# ThinkingAI Docs

> Product manual and integration guides for ThinkingAI: Agentic Engine and the analytics and engagement platform (dashboards, experiments, remote config, data governance), plus client/server SDKs and data import tools.

Every page is also available as plain Markdown. The links below point to the English Markdown of the latest version.

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- `{lang}` and its `{site}`:
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## Product manual (version 6.1, latest)

- [Agentic Engine user guide](https://docs.thinkingai.io/en/md/manual/README.md)
- [Agentic Engine](https://docs.thinkingai.io/en/md/manual/agent.md): Agentic Engine helps individuals and teams get work done through Agents: organize tasks, conversations, automations, and long-term memory in workspaces, and co…
- [Workspaces](https://docs.thinkingai.io/en/md/manual/workspace.md): Workspaces organize tasks, conversations, automations, and Space Memory around long-term goals, and hold the capabilities available in the space and the collab…
- [Space overview](https://docs.thinkingai.io/en/md/manual/workspace_overview.md): The space overview summarizes the tasks, conversations, space assets, and recent changes in the current workspace that need your attention, helping you quickly…
- [Create a space](https://docs.thinkingai.io/en/md/manual/create_workspace.md): This page describes how to create personal spaces and shared spaces, and the capability and permission settings to complete after creation.
- [Tasks](https://docs.thinkingai.io/en/md/manual/workspace_tasks.md): Tasks record the goals and issues in a workspace that need ongoing work, and organize related conversations and outputs into one working context.
- [Conversations](https://docs.thinkingai.io/en/md/manual/workspace_conversations.md): Conversations are the main entry point for collaborating with Agents in a workspace.
- [Automations](https://docs.thinkingai.io/en/md/manual/workspace_automation.md): Automations run Agent or Agent Team tasks repeatedly on a schedule in a workspace, and keep the conversation and results of each run.
- [Space Memory](https://docs.thinkingai.io/en/md/manual/workspace_memory.md): Space Memory captures information that stays useful to the current workspace over the long term, so that later conversations in the same space carry forward a…
- [Capability Center](https://docs.thinkingai.io/en/md/manual/capability_center.md): Capability Center centrally manages the capability resources available to Agents, including Agents, CLI, MCP, Skills, knowledge bases, and models.
- [Agent](https://docs.thinkingai.io/en/md/manual/agent_library.md): The Agent page is where you find, create, and manage Agents, and configure their models, instructions, and available capabilities.
- [Agent Team（Beta）](https://docs.thinkingai.io/en/md/manual/agent_team.md): Agent Team (Beta) organizes multiple Agents into a collaborative team that works on a task together in different execution modes.
- [Skill](https://docs.thinkingai.io/en/md/manual/skill_marketplace.md): The Skill page lets you find, install, and manage reusable task methods and workflows, and provide suitable Skills to Agents.
- [Models](https://docs.thinkingai.io/en/md/manual/model_management.md): The Models page lets you view and manage the models that Agents can use, including system-hosted models and company-level and personal model configurations.
- [MCP](https://docs.thinkingai.io/en/md/manual/mcp.md): MCP (Model Context Protocol) lets Agents connect to external tools and business services.
- [MCP authentication and configuration guide](https://docs.thinkingai.io/en/md/manual/mcp_integration.md): Date written: 2026-07-02.
- [Knowledge base](https://docs.thinkingai.io/en/md/manual/knowledge_base.md): Knowledge bases turn scattered business materials into knowledge assets that can be maintained continuously and used in Agent conversations.
- [CLI user guide](https://docs.thinkingai.io/en/md/manual/cli_guide.md): Parent section: Capability Center.
- [Channels and Integrations](https://docs.thinkingai.io/en/md/manual/channels_and_integrations.md): Channels and Integrations connects Agentic Engine to external collaboration platforms and manages the configuration, binding, and usage of each channel.
- [Channel overview and binding](https://docs.thinkingai.io/en/md/manual/channel_binding.md): This page explains how external messaging channels relate to personal account binding, and how users authorize and bind their own channel accounts after an adm…
- [Channel management](https://docs.thinkingai.io/en/md/manual/channel.md): Parent section: Channels and Integrations.
- [Feishu](https://docs.thinkingai.io/en/md/manual/feishu.md): On Feishu Open Platform, go to App details > Features > Bot and enable the bot feature.
- [Slack](https://docs.thinkingai.io/en/md/manual/slack.md): Slack requires HTTPS.
- [Lark](https://docs.thinkingai.io/en/md/manual/lark.md): For local testing, the redirect URL is: http://localhost:3000/api/lark-oauth/callback
- [DingTalk](https://docs.thinkingai.io/en/md/manual/dingtalk.md): Go to DingTalk Open Platform, log in, and follow these steps:
- [Discord](https://docs.thinkingai.io/en/md/manual/discord.md): Go to Discord Developer Portal and follow these steps:
- [WeCom](https://docs.thinkingai.io/en/md/manual/wecom.md): Log in to the WeCom Admin Console and configure it as follows:
- [Mattermost](https://docs.thinkingai.io/en/md/manual/mattermost.md): This article describes how to connect Mattermost to Agentic Engine.
- [WhatsApp channel user guide](https://docs.thinkingai.io/en/md/manual/whatsapp.md): This document is for Agentic Engine platform admins and regular users.
- [Google Chat bot setup and usage guide](https://docs.thinkingai.io/en/md/manual/google_chat.md): This document describes how to connect a Google Chat bot to Agentic Engine, and covers admin configuration, user binding, direct message and group chat usage,…
- [Zoom Team Chat configuration guide](https://docs.thinkingai.io/en/md/manual/zoom_team_chat.md): Go to Zoom App Marketplace and follow these steps:
- [Coding Agent](https://docs.thinkingai.io/en/md/manual/coding_agent.md): Parent section: Channel management.
- [Platform and Settings](https://docs.thinkingai.io/en/md/manual/platform_settings.md): Platform and Settings covers the runtime environment and system-level administration features.
- [My Sandbox](https://docs.thinkingai.io/en/md/manual/my_sandbox.md): My Sandbox shows the status, resource usage, working directories, and terminal of your personal runtime environment, and provides entry points for the necessar…
- [System Admin](https://docs.thinkingai.io/en/md/manual/agent_system_settings.md): System Admin is for members with admin permissions.
- [Developer Tools](https://docs.thinkingai.io/en/md/manual/developer_tools.md): Developer Tools covers how to use Agentic Engine from the command line or through other development methods.
- [AE CLI](https://docs.thinkingai.io/en/md/manual/cli.md): Parent section: Developer Tools.
- [Quick start](https://docs.thinkingai.io/en/md/manual/getting_started_menu.md): Agentic Engine (AE) is a new-generation intelligent big data engine for games that covers the full range of game scenarios.
- [Project preparation](https://docs.thinkingai.io/en/md/manual/pre_work.md): Before you start any of the steps, decide which project you will use for data reporting and analysis.
- [Create a tracking plan](https://docs.thinkingai.io/en/md/manual/set_properties.md): Before you connect data, you need to determine the user identification system that the project uses.
- [Report and validate data](https://docs.thinkingai.io/en/md/manual/send_data.md): Whichever reporting method you use, you need to find the APP_ID of the current project in Settings → Implementation in Project Settings and configure it before…
- [Next steps](https://docs.thinkingai.io/en/md/manual/support.md): After completing the previous steps, you can perform multidimensional cross analysis, build a user tag system, or run intelligent, fine-grained operations in A…
- [Analytics & Engage](https://docs.thinkingai.io/en/md/manual/user_guide_menu.md): This chapter describes the features of the AE platform in detail.
- [Dashboards](https://docs.thinkingai.io/en/md/manual/Dashboard.md): A dashboard brings together different reports on the same analysis topic, so you can see all the data on that topic on one page.
- [Create a dashboard](https://docs.thinkingai.io/en/md/manual/Creating_Dashboards.md): When you need to view data reports for multiple metrics on one page under a single analysis topic, you can create a dashboard.
- [Share dashboards](https://docs.thinkingai.io/en/md/manual/Sharing_Dashboards.md): You can share a single dashboard, share dashboards in bulk through a team space, and send data metrics to the relevant people on a schedule through dashboard d…
- [Dashboard digests: Feishu custom app bot setup](https://docs.thinkingai.io/en/md/manual/sharing_dashboards_feishu_bot_push_guide.md): When you use Send Now or Send Digest Updates for a dashboard and choose to send through a Feishu robot, you need a Feishu app that supports image uploads, and…
- [Manage dashboards](https://docs.thinkingai.io/en/md/manual/Managing_Dashboards.md): In the dashboard list, click the + button to the right of My Space and select New folder to create a dashboard folder.
- [Reports](https://docs.thinkingai.io/en/md/manual/Reports.md): In AE, analysis data is stored and presented through Reports.
- [Mobile](https://docs.thinkingai.io/en/md/manual/Mobile_End.md): AE users can access AE from their phones and view dashboard content on mobile.
- [Best practices](https://docs.thinkingai.io/en/md/manual/Best_Practice_of_Dashboards.md): Dashboard sharing is suitable when members share the data of a single dashboard with each other, while Team Space is suitable when members jointly follow and c…
- [Pre-computed dashboard FAQ](https://docs.thinkingai.io/en/md/manual/Qa_Scheduled_Dashboards.md): Reports in AE usually define a query Time Range.
- [Team space](https://docs.thinkingai.io/en/md/manual/Team_Space.md): Team spaces provide hierarchical management of and collaboration on the dashboards and BI dashboards in a project.
- [BI dashboards](https://docs.thinkingai.io/en/md/manual/bi_dashboard.md): A BI dashboard is a tool that combines data processing, chart creation, and personalized composition and layout to deliver rich visualizations around a specifi…
- [Create a BI dashboard](https://docs.thinkingai.io/en/md/manual/create_bi_dashboard.md): Similar to creating a dashboard, you can create a BI dashboard in My Space or a Team Space.
- [Preview, save drafts, and publish](https://docs.thinkingai.io/en/md/manual/publish_bi_dashboard.md): After you create a BI dashboard, it automatically enters edit mode, where you can edit sheets, pages, and components.
- [Sheets](https://docs.thinkingai.io/en/md/manual/work_sheet.md): A sheet is a table created in a BI dashboard from data within the project.
- [Catalog tables available for SQL sheets](https://docs.thinkingai.io/en/md/manual/bi_dashboard_table.md): The tables you can use to create sheets are called the Catalog.
- [Parameter controller](https://docs.thinkingai.io/en/md/manual/parameter_controller.md): A parameter controller is a component that lets viewers adjust the content of sheets.
- [Pages](https://docs.thinkingai.io/en/md/manual/bi_dashboard_component.md): Content in a BI dashboard is displayed on Pages.
- [Chart components](https://docs.thinkingai.io/en/md/manual/bi_dashboard_chart.md): A chart component is a component on a page that you use to build and display data charts.
- [Configure custom metrics with expressions](https://docs.thinkingai.io/en/md/manual/bi_dashboard_custom_metric.md): Besides dragging fields from the right and choosing an aggregation method, you can also add custom metrics directly.
- [Filter components](https://docs.thinkingai.io/en/md/manual/bi_dashboard_filter.md): A filter component is a component on a page that you use to filter charts.
- [Media components](https://docs.thinkingai.io/en/md/manual/bi_dashboard_media.md): In a dashboard, you can add media components such as images and web pages to a page to help viewers understand the data
- [Explore with dimension drill-down](https://docs.thinkingai.io/en/md/manual/bi_dashboard_drill.md): Dimension drill-down is an exploration path that goes from the big picture to the details.
- [Summary](https://docs.thinkingai.io/en/md/manual/summary_doc.md): A document is made up of multiple blocks, and each block corresponds to one content type.
- [Summary push](https://docs.thinkingai.io/en/md/manual/bi_dashboard_summary_push.md): Summary push supports:
- [Usage permissions](https://docs.thinkingai.io/en/md/manual/bi_dashboard_permission.md): BI dashboards are a separately sold AE suite, and you need a seat before you can use them.
- [Share a BI dashboard](https://docs.thinkingai.io/en/md/manual/bi_dashboard_share.md): By sharing a dashboard you've created, you can:
- [Access control](https://docs.thinkingai.io/en/md/manual/bi_dashboard_control.md): Access control applies row-level filtering to the sheets in a dashboard.
- [Third-party dashboard](https://docs.thinkingai.io/en/md/manual/third_party_bi_dashboard.md)
- [AI Beautify](https://docs.thinkingai.io/en/md/manual/ai_style.md): Where to find it
- [Dashboard AI assistant](https://docs.thinkingai.io/en/md/manual/AI_function_dashboard.md): Starting from v5.0, dashboards integrate AI capabilities that help you interpret data and get data insights faster.
- [Analytics](https://docs.thinkingai.io/en/md/manual/analysis_menu.md): The analytics module of Agentic Engine (AE) helps you run all kinds of analyses on data such as user behaviors and properties, so you can make better data-driv…
- [Basic concepts](https://docs.thinkingai.io/en/md/manual/basic_concepts.md): With the analysis module, you can quickly create specific metrics based on aggregate calculations of events and properties, display the resulting data as chart…
- [Calculation method logic](https://docs.thinkingai.io/en/md/manual/calculation_methods.md): When you configure the analysis metrics in Events Analysis, or the Also Show metrics in Retention Analysis or Distribution Analysis, you need to choose an appr…
- [Compare with group by](https://docs.thinkingai.io/en/md/manual/group_by.md): Comparison is a common analysis method, such as comparing data across different dimensions on the same date.
- [Filter data](https://docs.thinkingai.io/en/md/manual/filter.md): When you use an analysis model, you may want to analyze only the behavior of a specific group, pinpoint events that meet certain conditions, or exclude abnorma…
- [Analysis model options](https://docs.thinkingai.io/en/md/manual/operation.md): When you analyze data with a model, you can adjust some options to get data results that better fit your needs.
- [Events Analysis](https://docs.thinkingai.io/en/md/manual/event_analytics.md): Events Analysis is a powerful and flexible model.
- [View event details](https://docs.thinkingai.io/en/md/manual/event_detail.md): If you select the preset calculation method Event total, you can click an underlined number in the table to open the event details page.
- [Customize table display](https://docs.thinkingai.io/en/md/manual/table_display.md): Tables make it easy to view the exact values of your analysis metrics, and you can customize them as needed.
- [Compare data performance across dates](https://docs.thinkingai.io/en/md/manual/comparison_phase.md): In Events Analysis, besides comparing data across dimensions, you can also compare data performance across date phases.
- [Compare shares across dimensions](https://docs.thinkingai.io/en/md/manual/event_breakdown.md): If you want to see the share of paying users in a city out of all paying users, you can use a single-event filter to filter only the numerator by City is Beiji…
- [Use Extend Date Range](https://docs.thinkingai.io/en/md/manual/extend_date_range.md): This section describes how to use Extend Date Range in Events Analysis to configure metrics such as DAU/WAU and the ratio of daily revenue to the total revenue…
- [Retention Analysis](https://docs.thinkingai.io/en/md/manual/retention.md): Retention analysis is a common data analysis method that measures how different batches of new users perform, most commonly through the retention rate.
- [Calculate LT, LTV, and ROI](https://docs.thinkingai.io/en/md/manual/ltv_roi.md): Also Show is an advanced feature of Retention Analysis.
- [Overview calculation logic](https://docs.thinkingai.io/en/md/manual/retention_overview.md): The overview value summarizes retention over a period of time and helps you quickly understand how the data performs.
- [Retention Analysis visualization settings](https://docs.thinkingai.io/en/md/manual/retention_display.md): In addition to configuring the retention definition, you can use Customize Charts to display data in a way that better fits your analysis needs.
- [Funnel Analysis](https://docs.thinkingai.io/en/md/manual/funnel.md): Funnel Analysis is commonly used to observe conversion and churn at each step of a process.
- [Interval Analysis](https://docs.thinkingai.io/en/md/manual/interval.md): Interval Analysis analyzes the time interval between two events.
- [Distribution Analysis](https://docs.thinkingai.io/en/md/manual/distribution.md): Distribution Analysis aggregates the selected analysis entity by the number of times or days it completes events, or by event properties, and divides the resul…
- [Flows Analysis](https://docs.thinkingai.io/en/md/manual/path.md): Flows Analysis is an exploratory analysis that visually presents the sequence of user behaviors and key nodes in a Sankey diagram.
- [Composition Analysis](https://docs.thinkingai.io/en/md/manual/user_properties_analytics.md): Composition Analysis is a model designed specifically for statistical analysis of users and user properties.
- [Attribution Analysis](https://docs.thinkingai.io/en/md/manual/attribution.md): Attribution Analysis describes how much clicks on multiple in-app placements, or the occurrence of multiple events, contribute to a conversion event.
- [Scenarios - Leaderboard](https://docs.thinkingai.io/en/md/manual/leaderboard.md): Leaderboard analysis ranks a dimension by metric value.
- [Scenarios - Heatmap](https://docs.thinkingai.io/en/md/manual/heatmap.md): Heatmap is a model built specifically for game map analysis needs.
- [Scenarios - Revenue analysis](https://docs.thinkingai.io/en/md/manual/revenue.md): Revenue analysis shows the payment revenue, payment conversion, and cost recovery that a batch of entities generates over time after the first event.
- [SQL query](https://docs.thinkingai.io/en/md/manual/sql_ide.md): In addition to the analysis models described earlier, you can use SQL statements to perform advanced analysis that is hard to achieve with analysis models, and…
- [Use dynamic parameters](https://docs.thinkingai.io/en/md/manual/dynamic_parameters.md): Dynamic parameters let you adjust parts of a statement.
- [Advanced Trino SQL functions](https://docs.thinkingai.io/en/md/manual/trino.md): This section describes how to use advanced functions in Trino SQL.
- [Visualization module](https://docs.thinkingai.io/en/md/manual/visualization.md): The AE visualization module provides rich data processing and display capabilities.
- [User list](https://docs.thinkingai.io/en/md/manual/user_list.md): The user list shows detailed data of users who meet specific conditions.
- [Behavior sequence](https://docs.thinkingai.io/en/md/manual/user_streams.md): While you view macro-level data through analysis models, you can also use the behavior sequence to observe, at the micro level, how users with specific charact…
- [Best practices](https://docs.thinkingai.io/en/md/manual/analysis_best_practice.md): In practice, you can combine various models to analyze from different angles.
- [Engage](https://docs.thinkingai.io/en/md/manual/engage.md): The Engage module of Agentic Engine provides a solution for refined operations.
- [Operation tasks](https://docs.thinkingai.io/en/md/manual/operation_tasks.md): Operation tasks are a basic feature of the Agentic Engine Engage module.
- [Create operation tasks](https://docs.thinkingai.io/en/md/manual/creating_operation_tasks.md): Entry: Go to Engage > Operation Tasks > Create task > Select the Channel Type to open the operation task editing page.
- [Create scheduled tasks](https://docs.thinkingai.io/en/md/manual/creating_timed_tasks.md): Entry: Go to Engage > Operation Tasks > Create task > Select the Channel Type > Webhook / Push Notification > Select a channel to open the operation task editi…
- [Create triggered tasks (server-side)](https://docs.thinkingai.io/en/md/manual/creating_trigger_tasks.md): Triggered push applies real-time calculation to user behavior or status data collected in real time to find players who meet the specified behavior rule condit…
- [Create triggered tasks (client-side)](https://docs.thinkingai.io/en/md/manual/creating_client_trigger_tasks.md): In server-side triggered operation tasks, the timeliness of reporting data to the server makes it hard to cover scenarios in weakly connected games that requir…
- [Manage operation tasks](https://docs.thinkingai.io/en/md/manual/creating_operation_management.md): On the operation task list page, besides creating tasks, you can manage existing operation tasks or view their push records and task details.
- [Task effect analysis](https://docs.thinkingai.io/en/md/manual/task_effect_analysis.md): On the task effect analysis page, you can view the task configuration, A/B test report (if there is an A/B test), task data, task effect, and task cohorts.
- [Push experiments](https://docs.thinkingai.io/en/md/manual/ab_test.md): A/B testing is an experimental method that compares two or more different strategies, designs, or changes to determine which one has a greater impact on users…
- [Operation task time zone](https://docs.thinkingai.io/en/md/manual/operation_tasks_timezone.md): When multiple time zones are enabled for the project, you can specify the operation task time zone when you edit an operation task.
- [Journey](https://docs.thinkingai.io/en/md/manual/journey.md): Starting from V5.0, you can use journeys to customize end-to-end, multi-touchpoint, differentiated automated operation strategies through visual orchestration.
- [Create a journey](https://docs.thinkingai.io/en/md/manual/create_journey.md): This article describes how to create a journey.
- [Journey management](https://docs.thinkingai.io/en/md/manual/journey_manage.md): This article describes how to manage journeys.
- [Journey performance evaluation](https://docs.thinkingai.io/en/md/manual/journey_data.md): The journey data report includes overall journey data and node data.
- [Campaigns](https://docs.thinkingai.io/en/md/manual/campaigns.md): A campaign is a combination of multiple operation tasks that share the same operation goal.
- [Create a campaign](https://docs.thinkingai.io/en/md/manual/creating_campaigns.md): A campaign is a combination of multiple operation tasks that share the same operation goal.
- [Campaign management](https://docs.thinkingai.io/en/md/manual/campaign_management.md): This section describes how to manage campaigns in the interface, the campaign approval process, and campaign statuses and their corresponding actions (pause, e…
- [Campaign effect analysis](https://docs.thinkingai.io/en/md/manual/campaign_effect_analysis.md): The campaign effect analysis module provides campaign-level information and data reports, giving you a high-level view of the overall operation status and data…
- [Engage workspace](https://docs.thinkingai.io/en/md/manual/engage_workbench.md): The Engage workspace gives you a global view for monitoring the Engage module, helping operations staff understand the key operation metrics and the operation…
- [Engage overview metrics](https://docs.thinkingai.io/en/md/manual/operation_key_metrics.md): You can view the most important Engage metrics of this project directly on the Engage workspace to quickly understand the overall status of the project.
- [Engage schedule chart](https://docs.thinkingai.io/en/md/manual/schedule_chart.md): In the Workspace, below the metric cards, all running tasks and campaigns and their schedule information are displayed as a Gantt chart.
- [Engage settings](https://docs.thinkingai.io/en/md/manual/engage_settings.md): Engage settings provide management capabilities for the Engage module.
- [Access settings](https://docs.thinkingai.io/en/md/manual/engage_channel.md): The Engage module provides multiple ways to connect to downstream channels, all managed in Settings > Access Settings.
- [Channel settings for push tasks](https://docs.thinkingai.io/en/md/manual/channel_management.md): The Engage module currently supports four channel types: Webhook channels, Push Notification, Client Channel, and Third-party Platform channels (WeChat, KakaoT…
- [Get JPush app integration parameters](https://docs.thinkingai.io/en/md/manual/channel_management_jpush.md): Go to the JPush console and log in to your account.
- [Get an FCM server key](https://docs.thinkingai.io/en/md/manual/channel_management_fcm.md): After you configure the FCM channel, you can test how it works directly in Channel Settings.
- [Set up APNs push certificates](https://docs.thinkingai.io/en/md/manual/channel_management_apns.md): Go to the Apple Developer website and sign in with your developer account.
- [Config Center Channel Settings](https://docs.thinkingai.io/en/md/manual/config_channel_management.md): The AE Engage module provides the Config Center feature, which lets you update your app's appearance and in-app event content without releasing a new version.
- [Approval settings](https://docs.thinkingai.io/en/md/manual/approval_settings.md): Operation tasks take effect only after a second-level approval.
- [Whitelist management](https://docs.thinkingai.io/en/md/manual/white_list_management.md): On the Whitelist page, you can view and manage whitelists.
- [Analysis settings](https://docs.thinkingai.io/en/md/manual/preset_event_settings.md): On the Analysis Settings page, you can specify the core events used to automatically obtain related metrics on the Engage workbench, and configure the Frequent…
- [Localization settings](https://docs.thinkingai.io/en/md/manual/engage_localization.md): In localization settings, you can set the user language property so that the push content of operation tasks supports multiple languages.
- [Client parameters](https://docs.thinkingai.io/en/md/manual/client_parameters.md): Client parameters are parameters that the AE SDK can obtain directly.
- [Configuration table management](https://docs.thinkingai.io/en/md/manual/configuration_table.md): When configuring game push content, you often need to pick an enum value from a Dropdown Selection.
- [Operation task integration guide](https://docs.thinkingai.io/en/md/manual/engage_integration_docs.md)
- [Best practices](https://docs.thinkingai.io/en/md/manual/best_practices_engage.md): You can apply data insights to business scenarios through the Engage module and deliver personalized content to users at different stages, significantly improv…
- [Best practices for integrating WeChat mini game subscription messages](https://docs.thinkingai.io/en/md/manual/best_practices_engage_wechat_message.md): Mini games are a hot spot in today's game industry, and more and more game companies are entering the mini game market.
- [Config Center](https://docs.thinkingai.io/en/md/manual/config_center.md): Starting from V4.4, the AE Engage module provides the Config Center feature.
- [Config items](https://docs.thinkingai.io/en/md/manual/config_item.md): Each config item corresponds to a business module in your app, such as announcements, carousels, in-app messages, or the event center.
- [Config templates](https://docs.thinkingai.io/en/md/manual/config_template.md): Config templates carry business function parameters.
- [Config parameter management](https://docs.thinkingai.io/en/md/manual/config_paramater.md): Each config item has its own parameter namespace (that is, parameter names are unique within a config item but can repeat across config items).
- [Config strategies](https://docs.thinkingai.io/en/md/manual/config_strategy.md): An operation strategy is a specific config instance or a combination of instances, such as "Consecutive login reward config" and "Cumulative payment reward con…
- [Config effect analysis](https://docs.thinkingai.io/en/md/manual/config_strategy_analysis.md): Starting from V5.0, you can use event tracking and metric settings to analyze the effect of in-app content delivered through Config Center, and compare the eff…
- [Config Center technical integration docs](https://docs.thinkingai.io/en/md/manual/config_center_integration_docs.md)
- [Feature management](https://docs.thinkingai.io/en/md/manual/feature_flag.md): Go to Config Center → Feature.
- [User](https://docs.thinkingai.io/en/md/manual/user.md): The Users module provides a set of data tools that help you segment and filter users, giving you a quantitative basis for data-driven user engagement, marketin…
- [User tags](https://docs.thinkingai.io/en/md/manual/tag.md): User tags are one of the data tools the system provides for segmenting users.
- [Behavioral, first or last, and metric tags](https://docs.thinkingai.io/en/md/manual/behavioral_tag.md): There are 4 types of tags defined by data conditions: behavioral tags, first or last tags, metric tags, and SQL tags.
- [Tag date versions](https://docs.thinkingai.io/en/md/manual/tag_dates.md): For data condition tags, a user's tag value may differ each time the tag is calculated.
- [Cohorts](https://docs.thinkingai.io/en/md/manual/cohort.md): Cohorts are one of the data tools the system provides for segmenting users.
- [Behavioral cohorts](https://docs.thinkingai.io/en/md/manual/behavioral_cohort.md): Behavioral cohorts are mainly used to segment users by their behavior.
- [Real-time availability of cohorts](https://docs.thinkingai.io/en/md/manual/real_time_usage_status_in_cohorts.md): AE has gradually opened up various real-time applications that let you get information and carry out strategies based on users' real-time behavior.
- [User look-up](https://docs.thinkingai.io/en/md/manual/user_look_up.md): User look-up is a user data query tool provided by the system.
- [Data](https://docs.thinkingai.io/en/md/manual/data.md): The Data module lets you manage and query the data assets in the system.
- [Data management - events and properties](https://docs.thinkingai.io/en/md/manual/meta.md): User behavior data can be created in the system as three basic types of data assets, Events, Event Properties, and User Properties, and used by the analysis fe…
- [Event](https://docs.thinkingai.io/en/md/manual/meta_event.md): Use in analysis
- [Reported events](https://docs.thinkingai.io/en/md/manual/reported_event.md): List management page overview
- [Model-mapping events](https://docs.thinkingai.io/en/md/manual/allocated_event.md): List management page overview
- [Custom events](https://docs.thinkingai.io/en/md/manual/customEvent.md): On the Data > Management > Events page, you can view tracked events and custom events.
- [Event properties](https://docs.thinkingai.io/en/md/manual/event_prop.md): Use in analysis
- [Reported event properties](https://docs.thinkingai.io/en/md/manual/reported_event_prop.md): Reported event properties page overview
- [Model-mapping event properties](https://docs.thinkingai.io/en/md/manual/allocated_event_prop.md): Model-mapping event properties page overview
- [User property](https://docs.thinkingai.io/en/md/manual/user_prop.md): Use in analysis
- [Reported user properties](https://docs.thinkingai.io/en/md/manual/reported_user_prop.md): Reported user properties page overview
- [Model-mapping user properties](https://docs.thinkingai.io/en/md/manual/allocated_user_prop.md): Model-mapping user properties page overview
- [Batch editing of events and properties](https://docs.thinkingai.io/en/md/manual/meta_batch_edit.md): Batch editing
- [Custom properties and dimension table properties](https://docs.thinkingai.io/en/md/manual/customProperty.md): When you analyze business data, besides using properties that are reported or generated by model mapping directly, you may want to further process certain spec…
- [Best practices for creating custom properties](https://docs.thinkingai.io/en/md/manual/createCustomProperty.md): A custom property is a property created by performing secondary calculations on stored property fields with an SQL expression.
- [Scope of impact](https://docs.thinkingai.io/en/md/manual/impactScope.md): In the system, a data asset is often used in the data definition of another asset.
- [Real-time availability of events and properties](https://docs.thinkingai.io/en/md/manual/ProsAndEventOnRealTime.md): AE is gradually rolling out real-time applications that let you get information and act on strategies based on users' real-time behavior.
- [How do I save a CSV file in UTF-8 encoding?](https://docs.thinkingai.io/en/md/manual/utf8.md): As shown in the figure below, use UTF-8 encoding when saving, and set the file type to CSV
- [Data tables](https://docs.thinkingai.io/en/md/manual/DataTable.md): Data tables are one of the data ingestion methods the system provides; the other is SDK integration.
- [Associate data tables with properties](https://docs.thinkingai.io/en/md/manual/DataTableAsscoiate.md): Data tables can be used as dimension tables of event properties and user properties for analysis.
- [Real-time availability of data tables](https://docs.thinkingai.io/en/md/manual/DataTableOnRealTime.md): AE has gradually opened up various real-time applications that let you get information and carry out strategies based on users' real-time behavior.
- [Currency exchange](https://docs.thinkingai.io/en/md/manual/exchange.md): When your game business involves multiple currencies, reported event properties can contain amount data in multiple currencies.
- [Configure the exchange rate data source](https://docs.thinkingai.io/en/md/manual/exchangeDataSource.md): Converting between currencies requires timely and reliable exchange rates.
- [Standard currency code mapping](https://docs.thinkingai.io/en/md/manual/currency_code.md)
- [Metric](https://docs.thinkingai.io/en/md/manual/metric.md): Metrics are key to data analysis.
- [Tracking plan](https://docs.thinkingai.io/en/md/manual/plan.md): Before you analyze data, plan the events, event properties, and user properties to collect based on your analysis needs, and turn them into a tracking plan.
- [Project data processing rules](https://docs.thinkingai.io/en/md/manual/dataProcessRule.md): The system creates the data structures used for analysis when events and properties are reported for the first time.
- [Generate a tracking plan with AI](https://docs.thinkingai.io/en/md/manual/ai_generate_plan.md): When a project doesn't have a tracking plan yet, the AI Generate button appears in the empty state of the tracking plan page (projects that already have a trac…
- [Data validation](https://docs.thinkingai.io/en/md/manual/validation.md): For projects that have a tracking plan configured and already have reported data, you can validate whether the quality of the stored data meets expectations.
- [Reporting management](https://docs.thinkingai.io/en/md/manual/eventCounts.md): Here you can view how data has recently been received in the project, and disable or enable events.
- [Real-time data](https://docs.thinkingai.io/en/md/manual/realtime.md): Here you can view data reported in real time and promptly troubleshoot data reporting quality issues.
- [Debug mode](https://docs.thinkingai.io/en/md/manual/debug.md): Debug mode is designed to help developers debug data reporting and is intended only for data validation during the integration phase.
- [Third-party integration](https://docs.thinkingai.io/en/md/manual/thirdparty.md): The Third-party Integration module provides integration with a range of third-party ad platforms and can sync ad campaign and ad monetization data from these p…
- [Adjust integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_adjust.md): This article describes how to connect Adjust data in the AE backend.
- [Adjust real-time callbacks](https://docs.thinkingai.io/en/md/manual/thirdparty_adjust_callbacks.md): Adjust provides real-time callbacks for a range of events.
- [Adjust Report Service API](https://docs.thinkingai.io/en/md/manual/thirdparty_adjust_report_service_api.md): Adjust's Report Service API provides aggregated metric data, including cost, revenue, impressions, clicks, conversions, and more.
- [Adjust data integration solution](https://docs.thinkingai.io/en/md/manual/thirdparty_adjust_legacy.md): Last updated: 2023-03-24
- [Adjust FAQ (self-help)](https://docs.thinkingai.io/en/md/manual/thirdparty_adjust_faq.md): Issue: User property callbacks are configured for Adjust callback events, but the corresponding fields are missing from the user properties in the AE platform.
- [Best practices for troubleshooting user conversion failures in third-party callbacks](https://docs.thinkingai.io/en/md/manual/callback_conversion_troubleshooting.md): When customers connect and use third-party data callback solutions, they often run into user ID conversion failures.
- [Adjust attribution channel name shows Unattributed](https://docs.thinkingai.io/en/md/manual/thirdparty_adjust_unattributed.md): On June 17, 2025, Meta re-enabled AMM.
- [Apple Search Ads integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_applesearchads.md): This article describes how to connect Apple Search Ads data in the AE backend.
- [Apple Search Ads data integration solution](https://docs.thinkingai.io/en/md/manual/thirdparty_applesearchads_legacy.md): Last updated: 2022-07-18
- [AppLovin integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_applovin.md): This article describes how to connect AppLovin data in the AE backend.
- [AppLovin MAX S2S Impression Revenue API](https://docs.thinkingai.io/en/md/manual/thirdparty_applovin_max_s2s_impression_revenue_api.md): AppLovin provides a way to send back data through the MAX S2S Impression Revenue API.
- [AppLovin User Revenue API](https://docs.thinkingai.io/en/md/manual/thirdparty_applovin_user_revenue_api.md): In addition to the SDK and callback links, AppLovin also provides a data pull API, the User Revenue API, which supports pulling user-level or impression-level…
- [AppLovin Basic Reporting API](https://docs.thinkingai.io/en/md/manual/thirdparty_applovin_basic_reporting_api.md): In addition to user-level revenue data, AppLovin also provides an aggregated metrics API, the Basic Reporting API.
- [AppLovin Revenue Reporting API](https://docs.thinkingai.io/en/md/manual/thirdparty_applovin_revenue_reporting_api.md): AppLovin also provides an aggregated metrics API dedicated to Max monetization: the Revenue Reporting API.
- [AppLovin Cohort API integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_applovin_cohort_api.md): AppLovin's Cohort API returns day-N-after-install data similar to that of the Retention Analysis model, including monetization, impression, and other data for…
- [AppLovin Asset Reporting API](https://docs.thinkingai.io/en/md/manual/thirdparty_applovin_asset_reporting_api.md): AppLovin Asset Reporting API gets asset-level aggregated campaign data, including assets, campaigns, ad groups, impressions, clicks, and cost.
- [AppLovin data integration solution](https://docs.thinkingai.io/en/md/manual/thirdparty_applovin_legacy.md): Last updated: 2023-07-05
- [AppsFlyer integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_appsflyer.md): This article describes how to connect AppsFlyer data in the AE backend.
- [AppsFlyer Push API](https://docs.thinkingai.io/en/md/manual/thirdparty_appsflyer_push_api.md): Push API provides real-time AppsFlyer user-level data, including ad impression, click, install, and revenue data.
- [AppsFlyer Pull Raw Data](https://docs.thinkingai.io/en/md/manual/thirdparty_appsflyer_pull_raw_data.md): Pull API Raw Data can pull user-level data for a period of time.
- [AppsFlyer Pull API](https://docs.thinkingai.io/en/md/manual/thirdparty_appsflyer_pull_api.md): The AppsFlyer Pull API aggregated metrics API provides different types of aggregated metric data.
- [AppsFlyer Master API](https://docs.thinkingai.io/en/md/manual/thirdparty_appsflyer_master_api.md): Master API supports custom analysis dimensions and aggregated metrics, and is more flexible than the Pull API aggregated metrics API.
- [AppsFlyer Cohort API](https://docs.thinkingai.io/en/md/manual/thirdparty_appsflyer_cohort_api.md): The Cohort API is also an aggregated data API.
- [AppsFlyer data integration solution](https://docs.thinkingai.io/en/md/manual/thirdparty_appsflyer_legacy.md): Last updated: 2023-04-04
- [AppsFlyer FAQ (self-help)](https://docs.thinkingai.io/en/md/manual/thirdparty_appsflyer_faq.md): Add fields_whitelist to transfer in the format ["field_1", "field_2"] to control which fields are ingested:
- [DataX integration for S3 data](https://docs.thinkingai.io/en/md/manual/thirdparty_appsflyer_s3_datax.md): DataX plugin: s3reader
- [Firebase-BigQuery-GCS data migration technical solution](https://docs.thinkingai.io/en/md/manual/firebase_bigquery_gcs_migration.md): Last updated: 2022-04-13
- [Branch integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_branch.md): Branch provides Webhooks to send back user-level data.
- [Meta (Facebook) Ads integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_meta.md): Meta (that is, Facebook) provides the ad data pull API Facebook Ads Insights API, which supports getting basic report metrics for the ads you run on Meta, such…
- [Google AdMob integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_admob.md): The Google AdMob Reporting API returns aggregated monetization ad data, including monetization ad impressions, clicks, and revenue
- [Google Ads integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_googleads.md): Log in to the Google Ads dashboard with a Google Ads Manager Account, select TOOLS & SETTINGS - SETUP - API Center in the upper-right menu, and fill in the Goo…
- [Google Ads Developer Token application](https://docs.thinkingai.io/en/md/manual/thirdparty_googleads_token_faq.md): This document lists some of the questions in the Google Ads Developer Token application form.
- [ironSource integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_ironsource.md): This article describes how to connect ironSource data in the AE backend.
- [ironSource Impression Level Revenue API](https://docs.thinkingai.io/en/md/manual/thirdparty_ironsource_impression_level_revenue_api.md): Impression Level Revenue API provides user-level ad impression data.
- [ironSource Reporting API](https://docs.thinkingai.io/en/md/manual/thirdparty_ironsource_reporting_api.md): Reporting API is ironSource's aggregated metrics data API.
- [ironSource data integration solution](https://docs.thinkingai.io/en/md/manual/thirdparty_ironsource_legacy.md): Last updated: 2022-08-17
- [Kwai integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_kwai.md): The AE system currently supports connecting the ad creative data of Kwai, Kuaishou's overseas business platform, and supports getting aggregated metric data at…
- [Microsoft Advertising integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_bingads.md): Bing Ads API is the advertising API of Microsoft Advertising.
- [Mintegral integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_mintegral.md): The AE system currently supports connecting Mintegral ad campaign data.
- [Moloco integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_moloco.md): This article describes how to connect Moloco data in the AE backend.
- [Moloco Report API](https://docs.thinkingai.io/en/md/manual/thirdparty_moloco_report_api.md): Report API is an aggregated data API.
- [Moloco Log API](https://docs.thinkingai.io/en/md/manual/thirdparty_moloco_log_api.md): Log API provides user-level raw data with very rich user information.
- [Moloco data integration solution](https://docs.thinkingai.io/en/md/manual/thirdparty_moloco_legacy.md): Last updated: 2022-05-18
- [OPPO Marketing Platform integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_oppo.md): Currently, AE supports ingesting game detail data from OPPO Marketing Platform, including aggregated metrics such as cost, clicks, and impressions at the ad cr…
- [Singular integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_singular.md): Singular provides a partner postback feature, which you can use to send back user-level data, including attribution data, ad revenue, and conversion data
- [TalkingData integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_talkingdata.md): TalkingData provides a custom data callback feature, which we can use to get user-level activation or registration data
- [Tenjin integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_tenjin.md): This article describes how to connect Tenjin data in the AE backend.
- [Tenjin real-time callback API](https://docs.thinkingai.io/en/md/manual/thirdparty_tenjin_callbacks.md): Tenjin provides a way to configure real-time callback links.
- [Tenjin Reporting Metrics API](https://docs.thinkingai.io/en/md/manual/thirdparty_tenjin_reporting_metrics_api.md): Tenjin also provides an API for pulling aggregated metric data, the Reporting Metrics API, which provides:
- [TikTok integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_tiktok.md): This article describes how to connect TikTok data in the AE backend.
- [TikTok Basic Report](https://docs.thinkingai.io/en/md/manual/thirdparty_tiktok_basic_report.md): TikTok Basic Report provides aggregated grouping by ad dimensions.
- [TikTok Audience Report](https://docs.thinkingai.io/en/md/manual/thirdparty_tiktok_audience_report.md): Compared with Basic Report, TikTok Audience Report provides more aggregated grouping dimensions for users (called audience dimensions), but returns relatively…
- [TopOn integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_topon.md): This article describes how to connect TopOn data in the AE backend.
- [TopOn device-level data report](https://docs.thinkingai.io/en/md/manual/thirdparty_topon_device_report.md): The device-level data report gets data by user dimension, including users' total impressions, clicks, and revenue over a period of time.
- [TopOn full report query API](https://docs.thinkingai.io/en/md/manual/thirdparty_topon_full_report.md): The full report refers to the full report data in the TopOn data report query API.
- [TopOn data integration solution](https://docs.thinkingai.io/en/md/manual/thirdparty_topon_legacy.md): Last updated: 2022-08-17
- [TradPlus integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_tradplus.md): This article describes how to connect TradPlus data in the AE backend.
- [TradPlus device-level data report API](https://docs.thinkingai.io/en/md/manual/thirdparty_tradplus_device_reporting_api.md): The device-level data report API provides user-level ad monetization data, including metrics such as users' ad impressions, clicks, and revenue on a given day.
- [TradPlus full report query API](https://docs.thinkingai.io/en/md/manual/thirdparty_tradplus_reporting_api.md): The full report query API provides aggregated metric data for ad monetization, including metrics such as ad impressions, clicks, and revenue.
- [TradPlus data integration solution](https://docs.thinkingai.io/en/md/manual/thirdparty_tradplus_legacy.md): Last updated: 2022-08-22
- [Twitter Ads integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_twitter.md): The Twitter Ads Analytic API is an aggregated data API provided by Twitter.
- [Unity Ads integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_unity.md): This article describes how to connect Unity Ads data in the AE backend.
- [Unity Ads Advertising Statistics API](https://docs.thinkingai.io/en/md/manual/thirdparty_unity_v1.md): This plan sends Unity Ads ad delivery data back to Thinking Analytics (hereinafter the AE system) through the Advertising Statistics API.
- [Unity Ads Advertising Statistics API V2.0](https://docs.thinkingai.io/en/md/manual/thirdparty_unity_v2.md): This plan sends Unity Ads ad delivery data 2.0 back to Thinking Analytics (hereinafter the AE system) through the Advertising Statistics API v2.0.
- [vivo Marketing Platform integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_vivo.md): Currently, AE supports ingesting ad performance data from the vivo Marketing Platform Marketing API, including aggregated metrics such as cost, clicks, and imp…
- [Baidu Marketing data integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_baidu.md): The AE system currently supports connecting the Data Report (search promotion account report) of Baidu Marketing data, which provides metrics such as spend, cl…
- [Pangle Gromore integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_gromore.md): Pangle Gromore provides the aggregated data report API, which you can use to get aggregated impression, click, and revenue data for monetization ads
- [Ocean Engine integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_oceanengine.md): This article describes how to connect Ocean Engine data in the AE backend.
- [Ocean Engine all-in-one report](https://docs.thinkingai.io/en/md/manual/thirdparty_oceanengine_integrated_report.md): The all-in-one data report supports ad data at each ad granularity and at the material and keyword levels, with rich analysis dimensions and metrics.
- [Ocean Engine ad creative data](https://docs.thinkingai.io/en/md/manual/thirdparty_oceanengine_creative_report.md): Ad creative data is the standard data report with the finest ad data granularity.
- [Ocean Engine upgraded ad data report](https://docs.thinkingai.io/en/md/manual/thirdparty_oceanengine_custom_report.md): Upgraded ad data report is a new ad data report from Ocean Engine.
- [Ocean Engine data integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_oceanengine_legacy.md): This document describes how to send Ocean Engine data back to Agentic Engine (hereinafter the AE system).
- [Reyun TrackingIO integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_reyun.md): This article describes how to connect Reyun TrackingIO data in the AE backend.
- [SolarEngine integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_solarengine.md): Before you start connecting SolarEngine data, make sure that you have read the AE system's user identification rules and understand how AE identifies a user th…
- [Kuaishou Ads integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_kuaishou.md): This article describes how to connect Kuaishou Ads data in the AE backend.
- [Kuaishou advertiser data](https://docs.thinkingai.io/en/md/manual/thirdparty_kuaishou_account_report.md): Advertiser data provides various metrics at the advertiser level, including ad impressions, clicks, conversions, user acquisition cost, and many other metrics.
- [Kuaishou ad creative (custom) data](https://docs.thinkingai.io/en/md/manual/thirdparty_kuaishou_creative_report.md): The ad creative data (custom) report is suitable for getting data for ads whose Creative production method is Custom
- [Kuaishou programmatic creative 2.0 data](https://docs.thinkingai.io/en/md/manual/thirdparty_kuaishou_program_creative_report.md): Programmatic creative 2.0 data is suitable for getting data for ads whose Creative production method is Programmatic creative
- [Kuaishou Ads data integration solution](https://docs.thinkingai.io/en/md/manual/thirdparty_kuaishou_legacy.md): Last updated: 2022-07-27
- [Tencent Ads integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_tencent.md): This article describes how to connect Tencent Ads data in the AE backend.
- [Tencent daily report](https://docs.thinkingai.io/en/md/manual/thirdparty_tencent_daily_report.md): The Tencent Ads daily report supports sending back aggregated data, including metrics such as spend, clicks, and impressions
- [Tencent hourly report](https://docs.thinkingai.io/en/md/manual/thirdparty_tencent_hourly_report.md): The Tencent Ads hourly report supports sending back aggregated data at hourly granularity, including metrics such as spend, clicks, and impressions
- [Tencent new delivery daily report](https://docs.thinkingai.io/en/md/manual/thirdparty_tencent_daily_report_v3.md): The Tencent Ads new delivery daily report supports sending back aggregated data, including metrics such as spend, clicks, and impressions
- [Tencent new delivery hourly report](https://docs.thinkingai.io/en/md/manual/thirdparty_tencent_hourly_report_v3.md): The Tencent Ads new delivery hourly report supports sending back aggregated data at hourly granularity, including metrics such as spend, clicks, and impressions
- [WeChat mini game integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_wechat.md): This article describes how to connect WeChat mini game data in the AE backend.
- [WeChat mini game ad breakdown data integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_wechat_detail.md): The WeChat ad analytics data API provides a variety of data reports.
- [WeChat mini game ad summary data integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_wechat_summary.md): The WeChat ad analytics data API provides a variety of data reports.
- [Airbridge integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_airbridge.md): This article describes how to connect Airbridge data in the AE backend.
- [Airbridge real-time callback integration plan](https://docs.thinkingai.io/en/md/manual/thirdparty_airbridge_realtime.md): The Callbacks API provides real-time Airbridge user-level data, including ad impression, click, conversion, and other data.
- [Airbridge Actuals Report](https://docs.thinkingai.io/en/md/manual/thirdparty_airbridge_actuals_report.md): Airbridge Actuals Report provides aggregated report data, including metrics such as cost, impressions, clicks, and conversions.
- [Asset verification management](https://docs.thinkingai.io/en/md/manual/verify_assets.md): In the Assets > Assets Verification Management module, you can manage verification for all types of assets in a project (events, event properties, user propert…
- [Model Mapping Assets Configuration](https://docs.thinkingai.io/en/md/manual/asset_allocation.md): Model Mapping Assets Configuration: Converts cross-source data sources into data assets
- [Model-mapping tag table](https://docs.thinkingai.io/en/md/manual/route_field_desc_tag.md): When a business records players' tag information, there are two record structures: Wide table and tall table
- [Model-mapping dimension table](https://docs.thinkingai.io/en/md/manual/route_field_desc_dim.md): Model-mapping dimension table use case preview
- [Model-mapping entity table](https://docs.thinkingai.io/en/md/manual/route_field_desc_entity.md): ⚠ Because analysis model scenarios that involve the User Table are complex and data quality can greatly affect query performance, the data source and some fiel…
- [Model-mapping event table](https://docs.thinkingai.io/en/md/manual/route_field_desc_event.md): The AE standard event table data structure contains some key data columns, which affect how features of analysis models can be used later
- [Bulk upload of model-mapping configurations](https://docs.thinkingai.io/en/md/manual/route_field_desc_batch.md): Excel configuration upload overview
- [Model-mapping configuration: complex scenarios and SQL examples](https://docs.thinkingai.io/en/md/manual/spec_cross_field_sample.md): Common ways of recording time information and how to handle them:
- [Assets usage governance](https://docs.thinkingai.io/en/md/manual/asset_governance.md): List page description
- [Experiment](https://docs.thinkingai.io/en/md/manual/experiment.md): The experiment suite is a value-added feature of the AE system.
- [Experiment list](https://docs.thinkingai.io/en/md/manual/experiment_list.md): Go to Experiment → Experiments and click Create Experiment in the upper-right corner.
- [Traffic layers](https://docs.thinkingai.io/en/md/manual/traffic_layer.md): A traffic layer is a container that holds and allocates experiment traffic.
- [Metric management](https://docs.thinkingai.io/en/md/manual/experiment_metric_management.md): Go to Experiment → Metrics.
- [Experiment SDK integration guide](https://docs.thinkingai.io/en/md/manual/experiment_sdk_docs.md)
- [Session Replay](https://docs.thinkingai.io/en/md/manual/SessionReplay.md): This is a value-added feature.
- [Tools](https://docs.thinkingai.io/en/md/manual/Applications.md): In the Tool drop-down menu in the top bar, we provide the following features to help you get and view data metrics through AE more effectively:
- [Metric alerts](https://docs.thinkingai.io/en/md/manual/custom_alert.md): Metric alerts monitor the performance of key metrics and proactively send notifications when anomalies occur, helping you spot problems promptly and reduce unn…
- [Template Gallery](https://docs.thinkingai.io/en/md/manual/templates.md): In the Template Gallery, you can get AE best practices that ThinkingAI analysts have distilled from common business scenarios across industries.
- [Date annotations](https://docs.thinkingai.io/en/md/manual/annotation.md): You can annotate key dates in your project, such as version updates and major event launches.
- [Project settings](https://docs.thinkingai.io/en/md/manual/project_settings.md): Click the settings icon on the right side of the navigation bar to go to Project Settings.
- [Projects](https://docs.thinkingai.io/en/md/manual/project_implementation.md): On the Projects page, you can view and edit the project's basic information, picture, access parameters, and metadata overview, and view the project's usage da…
- [Member and permission management](https://docs.thinkingai.io/en/md/manual/project_permissions.md): Permissions in AE are divided into system permissions and project permissions, which are granted through system roles, and through project roles and data permi…
- [Member management](https://docs.thinkingai.io/en/md/manual/project_member.md): Project admins, Project Owners, and Root users can edit the members in a project, along with their roles and data permissions, for precise authorization.
- [Role management](https://docs.thinkingai.io/en/md/manual/project_role.md): A role contains operation permissions for a set of features.
- [Data permissions](https://docs.thinkingai.io/en/md/manual/project_data_access.md): Data permissions control the data that members can access in a project, enabling row-level and column-level data control.
- [Project time zone](https://docs.thinkingai.io/en/md/manual/project_time_zone.md): For projects that span multiple time zones (for example, when users come from different time zones or the business operates overseas), AE can uniformly identif…
- [Project entities](https://docs.thinkingai.io/en/md/manual/project_entities.md): An entity identifies unique users along different dimensions, such as device ID, account ID, character ID, and platform ID, for analysis.
- [Asset box management](https://docs.thinkingai.io/en/md/manual/project_asset_box.md): AE lets you pack the data assets of an existing project into an asset box and unpack it in a new project, so the new project is ready to use out of the box and…
- [Public link management](https://docs.thinkingai.io/en/md/manual/Public_Link.md): Set pages in AE as public links to allow public access without an account and help break down silos between departments.
- [Personal Center](https://docs.thinkingai.io/en/md/manual/personal_center.md): In Personal Center, you can view your account information and permissions, and use the Message Subscription module to choose which system messages you receive.
- [Message subscription](https://docs.thinkingai.io/en/md/manual/subscription.md): If some messages disturb you, go to Personal Center - Message Subscription, find the corresponding message scenes by Sending Module and Message Type, and then…
- [Agentic Engine Big Data Analytics System User Service Agreement](https://docs.thinkingai.io/en/md/manual/service_contract.md): Release date of this Agreement: September 22, 2022
- [ThinkingAI Privacy Policy](https://docs.thinkingai.io/en/md/manual/privacy_policy.md): Release date of this Privacy Policy: April 16, 2026
- [DataOps Platform](https://docs.thinkingai.io/en/md/manual/dataops_platform.md): Welcome to the Agentic Engine DataOps Platform.
- [Workbench](https://docs.thinkingai.io/en/md/manual/dataops_workbench.md): The Dashboard is an Agent-driven collaboration space for DataOps tasks.
- [Integration](https://docs.thinkingai.io/en/md/manual/dataops_integration.md): The Integration module is a core component of the AE DataOps Platform and handles data import and export.
- [Data source access](https://docs.thinkingai.io/en/md/manual/dataops_datasource.md): The data integration module supports fast and stable data synchronization between a wide range of heterogeneous data sources, such as MySQL, OSS, S3, Redis, an…
- [Configure a MySQL data source](https://docs.thinkingai.io/en/md/manual/dataops_datasource_mysql.md): MySQL is an open-source relational database management system that efficiently stores, manages, and queries large amounts of data.
- [Configure an OSS data source](https://docs.thinkingai.io/en/md/manual/dataops_datasource_oss.md): OSS (Object Storage Service) is a massive, secure, and highly reliable cloud storage service suitable for storing unstructured data.
- [Configure an S3 data source](https://docs.thinkingai.io/en/md/manual/dataops_datasource_s3.md): Amazon S3 (Simple Storage Service) is an object storage service provided by Amazon Web Services (AWS) and one of the most popular cloud storage solutions in th…
- [Configure a ClickHouse data source](https://docs.thinkingai.io/en/md/manual/dataops_datasource_clickhouse.md): ClickHouse is a column-oriented database management system (DBMS) with a highly specialized, modular, engine-based architecture.
- [Configure a Redis data source](https://docs.thinkingai.io/en/md/manual/dataops_datasource_redis.md): Redis is an open-source in-memory data structure store that is widely used as a database, cache, and message broker.
- [Configure a MongoDB data source](https://docs.thinkingai.io/en/md/manual/dataops_datasource_mongodb.md): Offline Sync plans in the AE DataOps Platform support writing (Writer) to MongoDB data sources.
- [Configure a SelectDB data source](https://docs.thinkingai.io/en/md/manual/dataops_datasource_selectdb.md): SelectDB Cloud is a new-generation, multi-cloud-native real-time data warehouse built on Apache Doris.
- [Configure a Feishu Bitable data source](https://docs.thinkingai.io/en/md/manual/dataops_datasource_larksheet.md): The AE DataOps Platform supports using Feishu Bitable as a data source and writing the data in its tables to the Built-in Warehouse for data synchronization.
- [Configure a StarRocks data source](https://docs.thinkingai.io/en/md/manual/dataops_datasource_starrocks.md): StarRocks is a high-performance analytical data warehouse that uses technologies such as vectorization, an MPP architecture, a CBO, intelligent materialized vi…
- [Configure a COS data source](https://docs.thinkingai.io/en/md/manual/dataops_datasource_cos.md): Tencent Cloud Object Storage (COS) stores object data such as files.
- [Configure a Google Sheets data source](https://docs.thinkingai.io/en/md/manual/dataops_datasource_google_sheets.md): The Google Sheets data source reads data from Google Sheets through Offline Sync and writes it to the platform's built-in data warehouse.
- [Offline Sync](https://docs.thinkingai.io/en/md/manual/dataops_batch_integration.md): After you create a data source, you can create an offline sync plan in the Offline Sync module to bring data from the data source into the DataOps Platform.
- [AE system data export](https://docs.thinkingai.io/en/md/manual/dataops_system_data_export.md): The AE system accumulates rich data assets, including:
- [Catalog](https://docs.thinkingai.io/en/md/manual/dataops_workspace_table.md): The Catalog module provides one-stop management of all table assets in the space, as well as centralized viewing and organizing of space resources.
- [Create and manage workspace tables](https://docs.thinkingai.io/en/md/manual/dataops_workspace_table_creation.md): Workspace tables are the core assets of the DataOps Platform and the scope of data that can be used directly in Flows of the current workspace, that is, the ta…
- [Partition table sync](https://docs.thinkingai.io/en/md/manual/dataops_partition_table_sync.md): Partition table sync updates the partition metadata of space tables with the partitions that can be discovered in external storage.
- [Batch create link views](https://docs.thinkingai.io/en/md/manual/dataops_link_batch_creation.md): To create link views for all the data in a database and quickly bring in your existing data system, use Batch Create Link View.
- [Development](https://docs.thinkingai.io/en/md/manual/dataops_development.md): The Dev module is the most critical module of the DataOps Platform and the one data developers use most often.
- [Flows](https://docs.thinkingai.io/en/md/manual/dataops_development_flow.md): A data warehouse typically has two kinds of business processes for data processing: Flows and temporary queries.
- [Create a Flow](https://docs.thinkingai.io/en/md/manual/dataops_development_create_flow.md): On the Flow list page, click + Flow in the upper-right corner to open a new tab for adding a Flow and start creating it.
- [Flow nodes](https://docs.thinkingai.io/en/md/manual/dataops_development_flow_node_type.md): In the AE DataOps Platform, Flow nodes are the basic units of a data processing workflow and can be understood as abstract representations of data processing t…
- [Flow scheduling settings](https://docs.thinkingai.io/en/md/manual/dataops_development_flow_schedule_setting.md): Flow Scheduling is where you configure how a Flow runs.
- [Flow parameter settings](https://docs.thinkingai.io/en/md/manual/dataops_development_flow_param.md): Flow parameters are an important concept in Flows.
- [Flow release](https://docs.thinkingai.io/en/md/manual/dataops_development_flow_release.md): This section describes the complete process of releasing a Flow and how to use the release list page.
- [Flow management and operations](https://docs.thinkingai.io/en/md/manual/dataops_development_flow_management.md): Click the tab to switch to the task node list, which shows details of the task nodes in all Flows in the current workspace.
- [Real-time tasks](https://docs.thinkingai.io/en/md/manual/dataops_development_realtime_task.md): By deeply integrating the powerful stream computing capabilities of Apache Flink, the AE DataOps Platform provides a higher-performance streaming data sync sol…
- [Operations](https://docs.thinkingai.io/en/md/manual/dataops_operation.md): The Ops module is where data developers and data operations staff view, manage, and monitor how Flows run online.
- [Instance management](https://docs.thinkingai.io/en/md/manual/dataops_operation_instance_management.md): After a Flow is released to the production environment, it can run manually or on a schedule.
- [Backfill jobs](https://docs.thinkingai.io/en/md/manual/dataops_operation_backfill.md): Backfill Jobs is a feature in the AE DataOps Platform for handling missing or updated data in specific scenarios.
- [Alerts](https://docs.thinkingai.io/en/md/manual/dataops_operation_alerts.md): Alerts deliver failure alerts for scheduled tasks directly to the people responsible.
- [IDE](https://docs.thinkingai.io/en/md/manual/dataops_IDE.md): The IDE module provides powerful data query capabilities.
- [DataApp](https://docs.thinkingai.io/en/md/manual/dataops_application.md): The DataApp module is key to getting the full value out of data in the DataOps Platform.
- [Data authorization](https://docs.thinkingai.io/en/md/manual/dataops_application_data_auth.md): Data warehouse processing produces many intermediate tables that aren't suitable for business use, and exposing all of them makes it harder for the business si…
- [Workspace Settings](https://docs.thinkingai.io/en/md/manual/dataops_space_management.md): A workspace is the basic unit for managing assets in the DataOps Platform.
- [Parameters](https://docs.thinkingai.io/en/md/manual/dataops_param_management.md): Workspace parameters are part of the parameter system and are scoped to the entire space; that is, all Flows, Offline Sync plans, and other modules in the spac…
- [Member management](https://docs.thinkingai.io/en/md/manual/dataops_member_management.md): The Member Management module lets you add members to or remove members from a workspace and assign them role permissions.
- [Role management](https://docs.thinkingai.io/en/md/manual/dataops_role_management.md): DataOps role management controls the scope of features that users can access and the operations they can perform in the DataOps Platform.
- [Space deletion](https://docs.thinkingai.io/en/md/manual/dataops_space_deletion.md): Space deletion cleans up DataOps spaces that are no longer used.
- [AI capabilities](https://docs.thinkingai.io/en/md/manual/AI_function.md)
- [Log interpretation assistant](https://docs.thinkingai.io/en/md/manual/AI_function_log_debug.md): The AI log interpretation assistant analyzes code and log content, interprets the errors in logs, and provides correct code examples or solutions, making devel…
- [AI same-structure table creation in DataOps](https://docs.thinkingai.io/en/md/manual/AI_function_table_ddl.md): DataOps Platform 5.1 adds AI same-structure table creation, which helps you create a new table in the target data source with the same structure as the source…
- [DataOps Platform release notes](https://docs.thinkingai.io/en/md/manual/dataops_release_note.md)
- [Omni Insights Platform](https://docs.thinkingai.io/en/md/manual/community_platform.md): Omni Insights Platform is designed for the community operations, marketing, game design, and R&D teams of games and apps.
- [Workbench](https://docs.thinkingai.io/en/md/manual/community_data_overview.md): The Workbench is the home page of the Omni Insights Platform, where you can view the content overview and key analysis results of the current space in one plac…
- [Analytics](https://docs.thinkingai.io/en/md/manual/community_explore.md): Analysis lets you run multi-dimensional statistics and comparisons on community content such as posts, videos, and comments, helping you understand content tre…
- [Visual analysis](https://docs.thinkingai.io/en/md/manual/community_analysis.md): Omni Insights Visual Analysis is the core feature module of the Omni Insights data analysis tool.
- [Risk management](https://docs.thinkingai.io/en/md/manual/community_risk_control.md): The risk management suite is a set of features tailored to game community operations.
- [Space settings](https://docs.thinkingai.io/en/md/manual/community_configuration.md): The Space Settings module includes the following core features:
- [Content center](https://docs.thinkingai.io/en/md/manual/community_content_center.md): Content Center brings together the community content you can view in a space.
- [Chat](https://docs.thinkingai.io/en/md/manual/community_chat.md)
- [Social media content](https://docs.thinkingai.io/en/md/manual/community_mentions.md): Social Media Content lets you find and view the posts, videos, and related comments collected in the current space.
- [Live streams](https://docs.thinkingai.io/en/md/manual/community_live_streams.md): Live Streams lets you view the live streaming data collected in a space.
- [Hot topics](https://docs.thinkingai.io/en/md/manual/community_hot.md): Hot Topics brings the daily summary and trending topics together to help you follow important discussions in the community and keep track of the topics you car…
- [Daily summary](https://docs.thinkingai.io/en/md/manual/community_daily_summary.md): Daily Summary is a core LLM-based content generation feature.
- [Trending Topics](https://docs.thinkingai.io/en/md/manual/community_trending_topics.md): Trending Topics is one of the core modules of the Omni Insights system.
- [Keywords](https://docs.thinkingai.io/en/md/manual/community_keywords.md)
- [Tags](https://docs.thinkingai.io/en/md/manual/community_tag.md): Content tags are an important data processing feature of the Omni Insights Platform, providing LLM-based custom data processing.
- [System Admin](https://docs.thinkingai.io/en/md/manual/system_settings.md): In System Settings, you can quickly get an overview of how the current AE system is being used and perform system-level operations and maintenance tasks.
- [General management](https://docs.thinkingai.io/en/md/manual/system_settings_general_management.md): In System Settings > General Management, you can view system usage and purchased products, configure the system, manage system member permissions, and monitor…
- [Usage and projects](https://docs.thinkingai.io/en/md/manual/system_projects_and_usage.md): On the Usage Overview and Projects pages under System Settings > Usage and Projects, you can view the data usage of the current AE system and manage all projec…
- [Usage overview](https://docs.thinkingai.io/en/md/manual/system_usage_overview.md): It includes the following:
- [Projects](https://docs.thinkingai.io/en/md/manual/system_projects_access.md): For all connected projects, you can view their creation time, metadata volume, and data usage in Projects.
- [DataOps space management](https://docs.thinkingai.io/en/md/manual/dataops_system_space_management.md): After the TE V5.0 upgrade, the system-level management capabilities of the DataOps Platform were merged into the System Settings module for unified management.
- [Member and permission management](https://docs.thinkingai.io/en/md/manual/system_member_management.md): In member and permission management under System Settings, Root users can manage all members and authorize members as System Admin to use some system managemen…
- [System Admin](https://docs.thinkingai.io/en/md/manual/system_admin.md): To make it easier for Root users to delegate AE system administration tasks, a Root user can assign the System Admin role to any member in the system and speci…
- [Data Warehouse Admin](https://docs.thinkingai.io/en/md/manual/dataops_warehouse_admin.md): This chapter describes the permissions of the Data Warehouse Admin role and how to manage it.
- [Seat management](https://docs.thinkingai.io/en/md/manual/biseat_manage.md): Root users, or system admins with the seat management permission, can assign seats to all members in the current system from the System Settings > General Mana…
- [System configuration](https://docs.thinkingai.io/en/md/manual/system_config.md): System configuration (now General Configuration in the left menu of System Settings) includes the Preferences, Email, Data Receiving URL, Login Options (shown…
- [SMTP email configuration](https://docs.thinkingai.io/en/md/manual/system_smtp.md): When you need to receive information from AE, such as message updates and dashboard digests, through your company's own email channel, a Root user in AE can co…
- [Data receiving URL management](https://docs.thinkingai.io/en/md/manual/system_receiving_url.md): This section describes how to manage global data receiving URLs on the System Settings page.
- [Third-party login](https://docs.thinkingai.io/en/md/manual/system_login_option.md): Starting with TE3.1, AE Root users can bind third-party apps in the System Settings module to:
- [Security center](https://docs.thinkingai.io/en/md/manual/system_security_center.md): AE improves the security of the system by supporting virtual MFA to verify login devices, page watermarks to mark screenshots taken in the system, and configur…
- [Virtual MFA](https://docs.thinkingai.io/en/md/manual/system_MFA.md): Virtual MFA is a widely used security verification method.
- [Watermark](https://docs.thinkingai.io/en/md/manual/system_watermark.md): If you need to add a watermark across the entire system to protect data security, you can enable the watermark feature.
- [Password policy](https://docs.thinkingai.io/en/md/manual/system_password.md): To improve system security and pass compliance reviews, Root users and system admins can configure password rules that apply to all members of the system in Sy…
- [System monitoring](https://docs.thinkingai.io/en/md/manual/system_monitor.md): You can monitor system performance: Use Query Statistics to monitor the details and performance overhead of queries made to the system, use Nodes to view the l…
- [Query statistics](https://docs.thinkingai.io/en/md/manual/system_query_stats.md): Note: Supported only in on-premises deployments.
- [Node monitoring](https://docs.thinkingai.io/en/md/manual/system_nodes.md): Use node monitoring to view the status of each host node in the current cluster, including CPU load, memory load, and hard disk load.
- [Service alerts](https://docs.thinkingai.io/en/md/manual/system_service_alerts.md): AE has detailed built-in service alert logic that helps you monitor your system comprehensively and sends alerts to the relevant people.
- [Warehouse management](https://docs.thinkingai.io/en/md/manual/system_settings_warehouse_management.md): The Warehouse Management module is designed for data operations staff and data warehouse admins to centrally configure and manage data warehouses in the DataOp…
- [Catalog authorization](https://docs.thinkingai.io/en/md/manual/system_catalog_auth.md): Before V5.0, data permissions in the data development environment had two major pain points:
- [Data integration](https://docs.thinkingai.io/en/md/manual/data_integration_docs.md)
- [Developer documentation](https://docs.thinkingai.io/en/md/manual/technical_document_menu.md): The developer documentation consists of two parts:
- [Secondary development tool](https://docs.thinkingai.io/en/md/manual/ta_tool.md): In version 2.8, the former data deletion tool was merged into the secondary development tool.
- [Data Deletion Tool](https://docs.thinkingai.io/en/md/manual/data_del.md): The Data Deletion Tool deletes data from the AE system.
- [Metadata Management Tool](https://docs.thinkingai.io/en/md/manual/modify_meta.md): The Metadata Management Tool is mainly used to change the type of, or delete, event properties and user properties in the AE system.
- [Data deduplication tool](https://docs.thinkingai.io/en/md/manual/dupevent_del.md): The data deduplication tool deduplicates duplicate event data in AE.
- [Data backfill](https://docs.thinkingai.io/en/md/manual/user_event_import.md): Data backfill queries data in the AE database with SQL statements and then writes the returned results back into the AE database to generate new events or new…
- [Custom table data import](https://docs.thinkingai.io/en/md/manual/data_transfer.md): In some cases, the data you need can't be represented as user or event data, such as mapping tables or external data.
- [Delete custom tables](https://docs.thinkingai.io/en/md/manual/drop_table.md): To delete a data table imported with the custom data import command, use the drop_table command to delete the custom table.
- [Importing external user properties by association](https://docs.thinkingai.io/en/md/manual/update_user_by_foreignkey.md): In some cases, you need to import external user data into the AE cluster, but the user identifier in the data isn't the #account_id or #distinct_id in the AE s…
- [Data archiving and reloading](https://docs.thinkingai.io/en/md/manual/ta_data_archive_and_reload.md): Data archiving migrates historical data, or data you don't need for now, to low-cost storage.
- [DataX engine](https://docs.thinkingai.io/en/md/manual/datax.md): DataX is an open-source project released by Alibaba (for details, visit the DataX GitHub homepage).
- [In-cluster plugins](https://docs.thinkingai.io/en/md/manual/inner_plugin_menu.md)
- [TaDataWriter plugin](https://docs.thinkingai.io/en/md/manual/ta-data-writer.md): TaDataWriter enables DataX to transfer data to the AE cluster.
- [TaJsonWriter plugin](https://docs.thinkingai.io/en/md/manual/ta-json-writer.md): TaJsonWriter writes files in AE JSON format to the local file system.
- [TaCustomTableWriter plugin](https://docs.thinkingai.io/en/md/manual/ta-customtable-writer.md): TACustomTableWriter lets you create custom tables in AE.
- [TaCustomReader plugin](https://docs.thinkingai.io/en/md/manual/ta-custom-reader.md): The TaCustomReader plugin enables DataX to read data from AE.
- [Out-of-cluster plugins](https://docs.thinkingai.io/en/md/manual/outer_plugin_menu.md)
- [TaDataxWriter plugin](https://docs.thinkingai.io/en/md/manual/ta-datax-writer.md): TaDataxWriter is a DataX writer plugin that lets you transfer data to the AE cluster within the DataX ecosystem.
- [Open API](https://docs.thinkingai.io/en/md/manual/open_api.md): This document covers advanced AE features and involves many technical details.
- [Model query API](https://docs.thinkingai.io/en/md/manual/query_api.md): This document covers advanced AE features and involves many technical details.
- [Events Analysis model API](https://docs.thinkingai.io/en/md/manual/event_query_api.md): For how to call the API, see the calling method described in the Open API document.
- [Retention Analysis model API](https://docs.thinkingai.io/en/md/manual/retention_query_api.md): For how to call the API, see the calling method described in the Open API document.
- [Funnel Analysis model API](https://docs.thinkingai.io/en/md/manual/funnel_query_api.md): For how to call the API, see the calling method described in the Open API document.
- [Distribution Analysis model API](https://docs.thinkingai.io/en/md/manual/distribution_query_api.md): For how to call the API, see the calling method described in the Open API document.
- [Flows Analysis model API](https://docs.thinkingai.io/en/md/manual/path_query_api.md): For how to call the API, see the calling method described in the Open API document.
- [Interval Analysis model API](https://docs.thinkingai.io/en/md/manual/interval_query_api.md): For how to call the API, see the calling method described in the Open API document.
- [Composition Analysis model API](https://docs.thinkingai.io/en/md/manual/user_prop_query_api.md): For how to call the API, see the calling method described in the Open API document.
- [Custom data query API](https://docs.thinkingai.io/en/md/manual/data_api.md): After you generate a query token, you can query project data by calling the custom query API.
- [Cohort and tag API](https://docs.thinkingai.io/en/md/manual/user_cluster_api.md): For how to call the API, see the calling method described in the Open API document.
- [Dimension table API](https://docs.thinkingai.io/en/md/manual/dimension_table_api.md): For how to call the API, see the calling method described in the Open API document.
- [Data table API](https://docs.thinkingai.io/en/md/manual/dataset_api.md): For how to call the API, see the calling method described in the Open API document.
- [SQL statement generation API](https://docs.thinkingai.io/en/md/manual/generate_sql_api.md): For how to call the API, see the calling method described in the Open API document.
- [Metadata management API](https://docs.thinkingai.io/en/md/manual/meta_data_manage_api.md): For how to call the API, see the calling method described in the Open API document.
- [Dashboard and report management API](https://docs.thinkingai.io/en/md/manual/dashboard_report_manage_api.md): For how to call the API, see the calling method described in the Open API document.
- [User management API](https://docs.thinkingai.io/en/md/manual/user_manage_api.md): For how to call the API, see the calling method described in the Open API document.
- [Project management API](https://docs.thinkingai.io/en/md/manual/project_manage_api.md): For how to call the API, see the calling method described in the Open API document.
- [Metric query API](https://docs.thinkingai.io/en/md/manual/metric_api.md): For how to call the API, see the calling method described in the Open API document.
- [Tracking management API](https://docs.thinkingai.io/en/md/manual/track_manage_api.md): For how to call the API, see the calling method described in the Open API document.
- [Model mapping configuration API](https://docs.thinkingai.io/en/md/manual/cross_source_config_api.md): For how to call the API, see the calling method described in the Open API document.
- [Privacy and security](https://docs.thinkingai.io/en/md/manual/te_privacy_compliance.md): Agentic Engine respects and protects people's data privacy and rights.
- [Google Play launch guide](https://docs.thinkingai.io/en/md/manual/te_googleplay.md): Other info
- [App Store launch guide](https://docs.thinkingai.io/en/md/manual/te_appstore.md): With iOS 14.3, Apple updated its privacy policy and requires publishers to fill in a privacy report when they update or release an app.
- [Release notes](https://docs.thinkingai.io/en/md/manual/release_note.md): The experiment suite is ThinkingEngine's newly developed suite of product features.

## Integration guides

- [Data integration](https://docs.thinkingai.io/en/md/integration/installation_menu.md): This section covers data collection in two parts.
- [Pre-integration preparation](https://docs.thinkingai.io/en/md/integration/pre_installation_menu.md): The AE (Agentic Engine) system provides a data integration solution that covers all platforms.
- [User identification rules](https://docs.thinkingai.io/en/md/integration/user_identify.md): Users may use your product on different devices and may also use it without logging in, which makes accurate user identification quite complex.
- [Data rules](https://docs.thinkingai.io/en/md/integration/data_format.md): This chapter describes the data structure, data types, and data limits of the AE backend in detail.
- [Preset properties and system fields](https://docs.thinkingai.io/en/md/integration/preset_properties.md): Preset properties are properties generated or obtained by AE.
- [Data collection guide](https://docs.thinkingai.io/en/md/integration/installation_guide.md): This section describes the ways to ingest data.
- [Client SDKs](https://docs.thinkingai.io/en/md/integration/client_sdk_menu.md): Client SDKs:
- [Android](https://docs.thinkingai.io/en/md/integration/android_sdk_installation.md): Latest version: 3.5.0
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/android_sdk_advanced.md): By default, the SDK instance uses a random UUID as each user's default distinct ID, which serves as the user's identifier when they are not logged in.
- [Auto-tracking](https://docs.thinkingai.io/en/md/integration/android_sdk_autotrack.md): The Android SDK supports auto-tracking of events such as install, start, and end.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/android_sdk_debug.md): During SDK integration, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/android_sdk_preset_properties.md): The following preset properties are carried by all events in the Android SDK, including auto-tracked events
- [Third-party data](https://docs.thinkingai.io/en/md/integration/android_sdk_thirdparty.md): The following sample code syncs data from multiple platforms:
- [Multiple instances](https://docs.thinkingai.io/en/md/integration/android_sdk_multi_appid.md): You can create SDK instances with multiple APP IDs, which we call multiple instances for short.
- [Compliance guide](https://docs.thinkingai.io/en/md/integration/android_sdk_compliance.md): In the section of your Privacy Policy on collecting and obtaining personal information, add the following content based on your actual situation.
- [Release notes](https://docs.thinkingai.io/en/md/integration/android_sdk_release_note.md): Update time: 2026/08/19 Download
- [iOS](https://docs.thinkingai.io/en/md/integration/ios_sdk_installation.md): Latest version: v3.5.3
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/ios_sdk_advanced.md): By default, the SDK uses DeviceID_InstallCount as each user's default distinct ID.
- [Auto-tracking](https://docs.thinkingai.io/en/md/integration/ios_sdk_autotrack.md): AE provides APIs for collecting data automatically.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/ios_sdk_debug.md): During SDK integration, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/ios_sdk_preset_properties.md): The following preset properties are carried by all events in the iOS SDK, including auto-tracked events
- [Third-party data](https://docs.thinkingai.io/en/md/integration/ios_sdk_thirdparty.md): Latest version: v0.3.5
- [Multiple instances](https://docs.thinkingai.io/en/md/integration/ios_sdk_multi_appid.md): iOS SDK 1.2.0 added support for multiple APPIDs.
- [Compliance guide](https://docs.thinkingai.io/en/md/integration/ios_sdk_compliance.md): In the section of your Privacy Policy on collecting and obtaining personal information, add the following content based on your actual situation.
- [Privacy manifest](https://docs.thinkingai.io/en/md/integration/ios_sdk_privacy_manifest.md): At WWDC23, Apple introduced a new privacy manifest policy.
- [Release notes](https://docs.thinkingai.io/en/md/integration/ios_sdk_release_note.md): Update time: 2026/09/22 Download
- [OpenHarmony](https://docs.thinkingai.io/en/md/integration/openharmony_sdk_installation.md): Latest version: 2.0.0
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/openharmony_sdk_advanced.md): By default, the SDK instance uses a random UUID as each user's default distinct ID, which serves as the user's identifier when they are not logged in.
- [Auto-tracking](https://docs.thinkingai.io/en/md/integration/openharmony_sdk_autotrack.md): The OpenHarmony SDK supports auto-tracking of events such as install, start, and end.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/openharmony_sdk_debug.md): During SDK integration, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/openharmony_sdk_preset_properties.md): The following preset properties are carried by all events in the OpenHarmony SDK, including auto-tracked events
- [Multiple instances](https://docs.thinkingai.io/en/md/integration/openharmony_sdk_multi_appid.md): You can create SDK instances with multiple APP IDs, which we call multiple instances for short.
- [Compliance guide](https://docs.thinkingai.io/en/md/integration/openharmony_sdk_compliance.md): Latest SDK version that meets the new regulatory requirements: 1.7.6
- [Release notes](https://docs.thinkingai.io/en/md/integration/openharmony_sdk_release_note.md): Update time: 2026/08/19 Download
- [JavaScript](https://docs.thinkingai.io/en/md/integration/javascript_sdk_installation.md): Latest version: v2.6.1
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/javascript_sdk_advanced.md): By default, the SDK instance uses a random number as each user's distinct ID, which serves as the user's identifier while the user is not logged in.
- [Auto-tracking](https://docs.thinkingai.io/en/md/integration/javascript_sdk_autotrack.md): To track click events on page elements, you can use trackLink to monitor HTML elements in batches:
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/javascript_sdk_debug.md): While integrating the SDK, you can debug in real time by viewing the SDK logs in the console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/javascript_sdk_preset_properties.md): The following preset properties are carried by all events in the JavaScript SDK, including auto-tracked events
- [Multiple instances](https://docs.thinkingai.io/en/md/integration/javascript_sdk_multi_appid.md): You can call the initInstance method to create a sub-instance object.
- [Compliance guide](https://docs.thinkingai.io/en/md/integration/javascript_sdk_compliance.md): In the section of your Privacy Policy on collecting and obtaining personal information, add the following content based on your actual situation.
- [Release notes](https://docs.thinkingai.io/en/md/integration/javascript_sdk_release_note.md): Update time: 2026/07/31 Download
- [Game engines](https://docs.thinkingai.io/en/md/integration/game_engine_sdk_installation.md)
- [Unity](https://docs.thinkingai.io/en/md/integration/unity_sdk_installation.md): Latest version: v3.5.3
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/unity_sdk_advanced.md): By default, the SDK instance uses a random UUID as each user's default distinct ID, which serves as the user's identifier when they are not logged in.
- [Auto-tracking](https://docs.thinkingai.io/en/md/integration/unity_sdk_autotrack.md): You can call EnableAutoTrack and pass in TDAutoTrackEventType to enable auto-tracking for the specified events.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/unity_sdk_debug.md): During SDK integration, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/unity_sdk_preset_properties.md): Preset properties collected on different platforms vary to some extent.
- [Third-party data](https://docs.thinkingai.io/en/md/integration/unity_sdk_thirdparty.md): Third-party data integration is supported starting from v2.4.0.
- [Multiple instances](https://docs.thinkingai.io/en/md/integration/unity_sdk_multi_appid.md): If you want to send data to multiple projects in your business, you can use the multiple instances feature that we provide.
- [Pluggable native SDK](https://docs.thinkingai.io/en/md/integration/unity_sdk_pluggable.md): By default, Objective-C code logic runs; after you switch, C# code logic runs.
- [Unity SDK user guide (legacy versions)](https://docs.thinkingai.io/en/md/integration/unity_sdk_installation_old.md): The Unity SDK has been upgraded to v2.0.0.
- [Compliance guide](https://docs.thinkingai.io/en/md/integration/unity_sdk_compliance.md): In the section of your Privacy Policy on collecting and obtaining personal information, add the following content based on your actual situation.
- [Release notes](https://docs.thinkingai.io/en/md/integration/unity_sdk_release_note.md): Update time: 2026/09/22 Download
- [Unreal](https://docs.thinkingai.io/en/md/integration/unreal_sdk_installation.md): Latest version: v3.0.3
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/unreal_sdk_advanced.md): By default, the SDK instance uses a random UUID as each user's default distinct ID, which serves as the user's identifier when they are not logged in.
- [Auto-tracking](https://docs.thinkingai.io/en/md/integration/unreal_sdk_autotrack.md): The TDAnalytics SDK currently supports auto-tracking of three events:
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/unreal_sdk_debug.md): During SDK integration, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/unreal_sdk_preset_properties.md): Preset properties collected on different platforms vary to some extent.
- [Third-party data](https://docs.thinkingai.io/en/md/integration/unreal_sdk_thirdparty.md): Third-party data integration is supported starting from v1.5.0.
- [Compliance guide](https://docs.thinkingai.io/en/md/integration/unreal_compliance.md): In the section of your Privacy Policy on collecting and obtaining personal information, add the following content based on your actual situation.
- [Release notes](https://docs.thinkingai.io/en/md/integration/unreal_sdk_release_note.md): Update time: 2025/10/11 Download
- [Cocos2d-x](https://docs.thinkingai.io/en/md/integration/cocos2d-x_sdk_installation.md): Latest version: v2.0.4
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/cocos2d-x_sdk_advanced.md): By default, the SDK instance uses a random UUID as each user's default distinct ID, which serves as the user's identifier when they are not logged in.
- [Auto-tracking](https://docs.thinkingai.io/en/md/integration/cocos2d-x_sdk_autotrack.md): The TDAnalytics SDK supports auto-tracking of three events:
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/cocos2d-x_sdk_debug.md): During SDK integration, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/cocos2d-x_sdk_preset_properties.md): Preset properties collected on different platforms vary to some extent.
- [Multiple instances](https://docs.thinkingai.io/en/md/integration/cocos2d-x_sdk_multi_appid.md): If you want to send data to multiple projects in your business, you can use the multiple instances feature that we provide.
- [Compliance guide](https://docs.thinkingai.io/en/md/integration/cocos2d-x_sdk_compliance.md): In the section of your Privacy Policy on collecting and obtaining personal information, add the following content based on your actual situation.
- [Release notes](https://docs.thinkingai.io/en/md/integration/cocos2d-x_sdk_release_note.md): Update time: 2026/02/04 Download
- [Cocos2d-Lua](https://docs.thinkingai.io/en/md/integration/cocos2d_lua_sdk_installation.md): Latest version: v2.0.2
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/cocos2d_lua_sdk_advanced.md): By default, the SDK instance uses a random number as each user's default distinct ID, which serves as the user's identifier while the user is not logged in.
- [Auto-tracking](https://docs.thinkingai.io/en/md/integration/cocos2d_lua_sdk_autotrack.md): The TDAnalytics SDK supports auto-tracking of three events:
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/cocos2d_lua_sdk_debug.md): After you enable logging, filter the ThinkingData logs in the IDE to observe the SDK's data reporting.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/cocos2d_lua_sdk_preset_properties.md): Preset properties collected on different platforms vary to some extent.
- [Compliance guide](https://docs.thinkingai.io/en/md/integration/cocos2d_lua_sdk_compliance.md): In the section of your Privacy Policy on collecting and obtaining personal information, add the following content based on your actual situation.
- [Release notes](https://docs.thinkingai.io/en/md/integration/cocos2d_lua_sdk_release_note.md): Update time: 2024/01/19 Download
- [CocosCreator](https://docs.thinkingai.io/en/md/integration/cocoscreator_sdk_installation.md): Latest version: v3.8.0
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/cocoscreator_sdk_advanced.md): By default, the SDK instance uses a random number as each user's distinct ID, which serves as the user's identifier while the user is not logged in.
- [Auto-tracking](https://docs.thinkingai.io/en/md/integration/cocoscreator_sdk_autotrack.md): Enable the events you want to auto-track in the config you use to create the instance, and the SDK automatically collects certain mini game behaviors.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/cocoscreator_sdk_debug.md): During SDK integration, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/cocoscreator_sdk_preset_properties.md): Preset properties collected on different platforms vary to some extent.
- [Native support](https://docs.thinkingai.io/en/md/integration/cocoscreator_sdk_native.md): When you build the iOS project for the first time, project code is generated in the ./build/ios/ and ./native/engine/ios/ directories.
- [Compliance guide](https://docs.thinkingai.io/en/md/integration/cocoscreator_sdk_compliance.md): In the section of your Privacy Policy on collecting and obtaining personal information, add the following content based on your actual situation.
- [Release notes](https://docs.thinkingai.io/en/md/integration/cocoscreator_sdk_release_note.md): Update time: 2026/09/16 Download
- [LayaAir](https://docs.thinkingai.io/en/md/integration/laya_sdk_installation.md): Latest version: v3.6.1
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/laya_sdk_advanced.md): By default, the SDK instance uses a random number as each user's distinct ID, which serves as the user's identifier while the user is not logged in.
- [Auto-tracking](https://docs.thinkingai.io/en/md/integration/laya_sdk_autotrack.md): Enable the events you want to auto-track in the config you use to create the instance, and the SDK automatically collects certain mini game behaviors.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/laya_sdk_debug.md): During SDK integration, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/laya_sdk_preset_properties.md): Preset properties collected on different platforms vary to some extent.
- [Native support](https://docs.thinkingai.io/en/md/integration/laya_sdk_native.md): When you initialize the SDK, add enableNative: true to config to enable Native support.
- [Release notes](https://docs.thinkingai.io/en/md/integration/laya_sdk_release_note.md): Update time: 2026/06/04 Download
- [Egret](https://docs.thinkingai.io/en/md/integration/egret_sdk_installation.md): Latest version: v3.0.2
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/egret_sdk_advanced.md): By default, the SDK instance uses a random number as each user's distinct ID, which serves as the user's identifier while the user is not logged in.
- [Auto-tracking](https://docs.thinkingai.io/en/md/integration/egret_sdk_autotrack.md): Enable the events you want to auto-track in the config you use to create the instance, and the SDK automatically collects certain mini game behaviors.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/egret_sdk_debug.md): During SDK integration, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of TA.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/egret_sdk_preset_properties.md): Preset properties collected on different platforms vary to some extent.
- [Native support](https://docs.thinkingai.io/en/md/integration/egret_sdk_native.md): Build the iOS app and configure the iOS project
- [Release notes](https://docs.thinkingai.io/en/md/integration/egret_sdk_release_note.md): Update time: 2024/02/09 Download
- [Corona](https://docs.thinkingai.io/en/md/integration/corona_sdk_installation.md): Latest version: v2.0.1
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/corona_sdk_advanced.md): By default, the SDK instance uses a random number as each user's default distinct ID, which serves as the user's identifier while the user is not logged in.
- [Auto-tracking](https://docs.thinkingai.io/en/md/integration/corona_sdk_autotrack.md): The TDAnalytics SDK supports auto-tracking of three events:
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/corona_sdk_debug.md): After you enable logging, filter the ThinkingData logs in the IDE to observe the SDK's data reporting.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/corona_sdk_preset_properties.md): Preset properties collected on different platforms vary to some extent.
- [Compliance guide](https://docs.thinkingai.io/en/md/integration/corona_sdk_compliance.md): In the section of your Privacy Policy on collecting and obtaining personal information, add the following content based on your actual situation.
- [Release notes](https://docs.thinkingai.io/en/md/integration/corona_sdk_release_note.md): Update time: 2023/11/24 Download
- [Mini programs & mini games](https://docs.thinkingai.io/en/md/integration/mp_sdk_installation.md): Latest version: v3.8.1 Download (mini program) Download (mini game)
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/mp_sdk_advanced.md): By default, the SDK instance uses a random number as each user's distinct ID, which serves as the user's identifier while the user is not logged in.
- [Auto-tracking](https://docs.thinkingai.io/en/md/integration/mp_sdk_autotrack.md): Since v1.2.0, we provide auto-tracking.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/mp_sdk_debug.md): While integrating the SDK, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/mp_sdk_preset_properties.md): The following preset properties are carried by all events (including auto-tracked events) in the Mini Program/Mini Game SDK
- [Multiple instances](https://docs.thinkingai.io/en/md/integration/mp_sdk_multi_appid.md): Starting from v1.3.0, this SDK supports multiple instances.
- [Compliance guide](https://docs.thinkingai.io/en/md/integration/mp_sdk_compliance.md): In the section of your Privacy Policy on collecting and obtaining personal information, add the following content based on your actual situation.
- [Release notes](https://docs.thinkingai.io/en/md/integration/mp_sdk_release_note.md): Update time: 2026/09/29 Mini program Mini game
- [Cross-platform frameworks](https://docs.thinkingai.io/en/md/integration/app_third_support.md)
- [React Native](https://docs.thinkingai.io/en/md/integration/rn_sdk_support.md): This guide shows you how to use the SDK features in React Native.
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/rn_sdk_advanced.md): By default, the SDK instance uses a random UUID as each user's default distinct ID, which serves as the user's identifier when they are not logged in.
- [Auto-tracking](https://docs.thinkingai.io/en/md/integration/rn_sdk_autotrack.md): You can call enableAutoTrack and pass in a TDAutoTrackEventType type to enable auto-tracking.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/rn_sdk_debug.md): While integrating the SDK, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/rn_sdk_preset_properties.md): The preset properties collected on the iOS and Android platforms differ to some extent.
- [Compliance guide](https://docs.thinkingai.io/en/md/integration/rn_sdk_compliance.md): In the section of your Privacy Policy on collecting and obtaining personal information, add the following content based on your actual situation.
- [Release notes](https://docs.thinkingai.io/en/md/integration/rn_sdk_release_note.md): Update time: 2026/05/14
- [Flutter](https://docs.thinkingai.io/en/md/integration/flutter_sdk_installation.md): This guide describes how to integrate the Flutter SDK into your project.
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/flutter_sdk_advanced.md): By default, the SDK instance uses a random UUID as each user's default distinct ID, which serves as the user's identifier when they are not logged in.
- [Auto-tracking](https://docs.thinkingai.io/en/md/integration/flutter_sdk_autotrack.md): You can call enableAutoTrack and pass in a TDAutoTrackEventType type to enable auto-tracking.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/flutter_sdk_debug.md): During SDK integration, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/flutter_sdk_preset_properties.md): The preset properties collected on the iOS and Android platforms differ to some extent.
- [Compliance guide](https://docs.thinkingai.io/en/md/integration/flutter_sdk_compliance.md): In the section of your Privacy Policy on collecting and obtaining personal information, add the following content based on your actual situation.
- [Release notes](https://docs.thinkingai.io/en/md/integration/flutter_sdk_release_note.md): Update time: 2026/08/05
- [uni-app](https://docs.thinkingai.io/en/md/integration/uniapp_sdk_installation.md): Latest version: 3.6.0 Download
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/uniapp_sdk_advanced.md): By default, the SDK instance uses a random number as each user's distinct ID, which serves as the user's identifier while the user is not logged in.
- [Auto-tracking](https://docs.thinkingai.io/en/md/integration/uniapp_sdk_autotrack.md): We provide auto-tracking.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/uniapp_sdk_debug.md): While integrating the SDK, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/uniapp_sdk_properties.md): The following preset properties are carried by all events on uni-app mini program platforms, including auto-tracked events
- [Multiple instances](https://docs.thinkingai.io/en/md/integration/uniapp_sdk_multi_appid.md): This SDK supports multiple instances.
- [Native support](https://docs.thinkingai.io/en/md/integration/uniapp_sdk_native.md): Import td-analytics in uni_modules to support native platforms.
- [Release notes](https://docs.thinkingai.io/en/md/integration/uniapp_sdk_release_note.md): Update time: 2026/04/14 Download
- [C++](https://docs.thinkingai.io/en/md/integration/client_cpp_sdk_installation.md): Latest version: v1.5.3
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/client_cpp_sdk_advanced.md): By default, the SDK instance uses a random number as each user's default distinct ID, which serves as the user's identifier while the user is not logged in.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/client_cpp_sdk_debug.md): During SDK integration, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Release notes](https://docs.thinkingai.io/en/md/integration/client_cpp_sdk_release_note.md): Update time: 2025/10/11 Download
- [C#](https://docs.thinkingai.io/en/md/integration/client_csharp_sdk_installation.md): Latest version: 2.0.1
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/client_csharp_sdk_advanced.md): By default, the SDK instance uses a random UUID as each user's default distinct ID, which serves as the user's identifier when they are not logged in.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/client_csharp_sdk_debug.md): During SDK integration, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Release notes](https://docs.thinkingai.io/en/md/integration/client_csharp_sdk_release_note.md): Update time: 2025/10/13 Download
- [macOS](https://docs.thinkingai.io/en/md/integration/macos_sdk_installation.md): Latest version: v3.0.4
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/macos_sdk_advanced.md): By default, an SDK instance uses DeviceID_InstallCount as each user's default distinct ID.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/macos_sdk_debug.md): During SDK integration, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/macos_sdk_preset_properties.md): The following preset properties are carried by all events in the SDK
- [Connect H5 with the app SDK](https://docs.thinkingai.io/en/md/integration/h5_app_integrate.md): An app may contain some pages built with H5.
- [Client SDK FAQ](https://docs.thinkingai.io/en/md/integration/client_sdk_faq.md): Data from native client SDKs (including Unity, Unreal, Flutter, and others) is first cached in a local database, and data reporting is triggered in the followi…
- [Server-side SDK](https://docs.thinkingai.io/en/md/integration/server_sdk_menu.md): Server-side SDKs:
- [Java](https://docs.thinkingai.io/en/md/integration/java_sdk_installation.md): Latest version: v3.0.4-beta.1
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/java_sdk_advanced.md): After the SDK is initialized, you can track data to collect user behavior information.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/java_sdk_debug.md): During SDK integration, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/java_sdk_preset_properties.md): The following preset properties are carried by all events in the Java SDK.
- [Release notes](https://docs.thinkingai.io/en/md/integration/java_sdk_release_note.md): Update time: 2026/01/07
- [Golang](https://docs.thinkingai.io/en/md/integration/golang_sdk_installation.md): Latest version: v2.3.0
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/golang_sdk_advanced.md): After the SDK is initialized, you can start tracking data to collect user behavior.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/golang_sdk_debug.md): During SDK integration, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/golang_sdk_preset_properties.md): The following preset properties are carried by all events in the Golang SDK.
- [Release notes](https://docs.thinkingai.io/en/md/integration/golang_sdk_release_note.md): Update time: 2026/03/17
- [C](https://docs.thinkingai.io/en/md/integration/c_sdk_installation.md): Latest version: v2.0.0
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/c_sdk_advanced.md): After the SDK is initialized, you can start tracking data to collect user behavior.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/c_sdk_debug.md): During SDK integration, you can use the AE Debug feature for real-time debugging.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/c_sdk_preset_properties.md): The following preset properties are carried by all events in the C SDK.
- [Release notes](https://docs.thinkingai.io/en/md/integration/c_sdk_release_note.md): Update time: 2023/11/30
- [C#](https://docs.thinkingai.io/en/md/integration/csharp_sdk_installation.md): Latest version: v2.0.3
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/csharp_sdk_advanced.md): After the SDK is initialized, you can start tracking data to collect user behavior.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/csharp_sdk_debug.md): During SDK integration, you can use the AE Debug feature for real-time debugging.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/csharp_sdk_preset_properties.md): The following preset properties are carried by all events in the C# SDK.
- [Release notes](https://docs.thinkingai.io/en/md/integration/csharp_sdk_release_note.md): Update time: 2025/09/03
- [Erlang](https://docs.thinkingai.io/en/md/integration/erlang_sdk_installation.md): This guide shows you how to integrate the Erlang SDK into your project.
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/erlang_sdk_advanced.md): After the SDK is initialized, you can start tracking data to collect user behavior.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/erlang_sdk_debug.md): During SDK integration, you can use the AE Debug feature for real-time debugging.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/erlang_sdk_preset_properties.md): The following preset properties are carried by all events in the Erlang SDK.
- [Release notes](https://docs.thinkingai.io/en/md/integration/erlang_sdk_release_note.md): Update time: 2023/10/08
- [Ruby](https://docs.thinkingai.io/en/md/integration/ruby_sdk_installation.md): This guide shows you how to integrate the Ruby SDK into your project.
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/ruby_sdk_advanced.md): After the SDK is initialized, you can start tracking data to collect user behavior.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/ruby_sdk_debug.md): During SDK integration, you can use the AE Debug feature for real-time debugging.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/ruby_sdk_preset_properties.md): The following preset properties are carried by all events in the Ruby SDK.
- [Release notes](https://docs.thinkingai.io/en/md/integration/ruby_sdk_release_note.md): Update time: 2026/06/05
- [Lua](https://docs.thinkingai.io/en/md/integration/lua_sdk_installation.md): This guide shows you how to integrate the Lua SDK into your project.
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/lua_sdk_advanced.md): After the SDK is initialized, you can start tracking data to collect user behavior.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/lua_sdk_debug.md): During SDK integration, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/lua_sdk_preset_properties.md): The following preset properties are carried by all events in the Lua SDK.
- [Release notes](https://docs.thinkingai.io/en/md/integration/lua_sdk_release_note.md): Update time: 2026/01/08
- [Node.js](https://docs.thinkingai.io/en/md/integration/nodejs_sdk_installation.md): This guide describes how to integrate the Node.js SDK into your project.
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/nodejs_sdk_advanced.md): After the SDK is initialized, you can start tracking data to collect user behavior.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/nodejs_sdk_debug.md): During SDK integration, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/nodejs_sdk_preset_properties.md): The following preset properties are carried by all events in the Node SDK.
- [Release notes](https://docs.thinkingai.io/en/md/integration/nodejs_sdk_release_note.md): Update time: 2024-03-26
- [PHP](https://docs.thinkingai.io/en/md/integration/php_sdk_installation.md): Latest version: v3.1.1
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/php_sdk_advanced.md): After the SDK is initialized, you can start tracking data to collect user behavior.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/php_sdk_debug.md): During SDK integration, you can use the AE Debug feature for real-time debugging.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/php_sdk_preset_properties.md): The following preset properties are carried by all events in the PHP SDK.
- [Release notes](https://docs.thinkingai.io/en/md/integration/php_sdk_release_note.md): Update time: 2024/07/24
- [Python](https://docs.thinkingai.io/en/md/integration/python_sdk_installation.md): This guide describes how to integrate the Python SDK into your project.
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/python_sdk_advanced.md): After the SDK is initialized, you can start tracking data to collect user behavior.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/python_sdk_debug.md): During SDK integration, you can debug in real time by viewing the SDK logs in the IDE console or by using the Debug feature of AE.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/python_sdk_preset_properties.md): The following preset properties are carried by all events in the Python SDK.
- [Release notes](https://docs.thinkingai.io/en/md/integration/python_sdk_release_note.md): Update time: 2023/10/08
- [C++](https://docs.thinkingai.io/en/md/integration/cpp_server_sdk_installation.md): Latest version: v2.0.0
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/cpp_server_sdk_advanced.md): After the SDK is initialized, you can start tracking data to collect user behavior.
- [Real-time debugging](https://docs.thinkingai.io/en/md/integration/cpp_server_sdk_debug.md): During SDK integration, you can use the AE Debug feature for real-time debugging.
- [Preset properties](https://docs.thinkingai.io/en/md/integration/cpp_server_sdk_preset_properties.md): The following preset properties are carried by all events in the C++ SDK.
- [Release notes](https://docs.thinkingai.io/en/md/integration/cpp_server_sdk_release_note.md): Update time: 2023/11/30
- [Data import](https://docs.thinkingai.io/en/md/integration/data_import_menu.md): The main data import tools are:
- [LogBus2 guide](https://docs.thinkingai.io/en/md/integration/logbus2_installation.md): LogBus2 is a log synchronization tool redeveloped on the basis of the original LogBus.
- [Alert configuration demo](https://docs.thinkingai.io/en/md/integration/logbus2_alert_demo.md)
- [Monitoring configuration demo](https://docs.thinkingai.io/en/md/integration/logbus2_monitor_demo.md): The LogBus2 monitoring feature depends on Prometheus, Pushgateway, and Grafana.
- [Plugin configuration demo](https://docs.thinkingai.io/en/md/integration/logbus2_plugin_demo.md): Configuration explained:
- [Filebeat + Logstash user guide](https://docs.thinkingai.io/en/md/integration/filebeat_logstash_installation.md): This section describes how to use the data transfer tool Filebeat + Logstash:
- [Ta-Datax-Writer plugin user guide](https://docs.thinkingai.io/en/md/integration/datax_writer_installation.md): Ta-Datax-Writer is a DataX writer plugin that lets you transfer data to the AE cluster within the DataX ecosystem.
- [LogBus guide](https://docs.thinkingai.io/en/md/integration/logbus_legacy_installation.md): This section describes how to use the data transfer tool LogBus:
- [LogBus Windows version guide](https://docs.thinkingai.io/en/md/integration/logbus_windows_installation.md): This section describes how to use the Windows version of the data transfer tool LogBus:
- [RESTful API user guide](https://docs.thinkingai.io/en/md/integration/restful_api.md): This guide describes how to use the data ingestion API.
- [About GDPR](https://docs.thinkingai.io/en/md/integration/about_gdpr.md): On May 25, 2018, the EU's General Data Protection Regulation (GDPR) officially took effect.
- [ThinkingData SDK privacy statement](https://docs.thinkingai.io/en/md/integration/privacy_cn.md): Release date of this Privacy Statement: December 23, 2025
- [SDK Information Collection Rules](https://docs.thinkingai.io/en/md/integration/privacy.md): ThinkingData operates the www.thinkingdata.cn website, which provides the SERVICE.
- [Advanced data types](https://docs.thinkingai.io/en/md/integration/advanced_data_type.md): This section describes the advanced data types in AE.
- [Updatable events](https://docs.thinkingai.io/en/md/integration/track_update_and_track_overwrite.md): This section describes how to use updatable events, a special data structure in the AE system.
- [First-event check](https://docs.thinkingai.io/en/md/integration/first_check_id.md): This section describes how to use a special data structure of the AE system: the first-event check.
- [Operation task integration guide](https://docs.thinkingai.io/en/md/integration/integration_engage.md): Operation tasks currently support channel types such as Webhook channels, push notifications, client channels, and third-party platforms.
- [Webhook channel integration guide](https://docs.thinkingai.io/en/md/integration/webhook_connection.md): The Webhook channel of the AE Engage module defines an API for connecting to any downstream messaging or message-like system on the customer side.
- [Push notification integration](https://docs.thinkingai.io/en/md/integration/push_connection.md): This section describes in detail how to integrate push notification channels for devices such as Android, iOS, and Unity.
- [Android push notification integration](https://docs.thinkingai.io/en/md/integration/android_push.md): In the automatic collection solution, the SDK internally reports the push tokens and push message click events (te_ops_push_click) of each platform (currently…
- [iOS push notification integration](https://docs.thinkingai.io/en/md/integration/ios_push.md): Release version: v1.1.2 Framework download
- [Unity push notification integration](https://docs.thinkingai.io/en/md/integration/unity_push.md): Upload the push click event when the user clicks the notification.
- [Client-triggered SDK integration guide](https://docs.thinkingai.io/en/md/integration/client_connection.md): Client-triggered capabilities rely on the ThinkingData SDK.
- [Android](https://docs.thinkingai.io/en/md/integration/android_td_sdk.md): Latest version: v1.4.1
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/android_td_sdk_advanced.md): The TDSettings configuration passed in during initialization is described below
- [Release notes](https://docs.thinkingai.io/en/md/integration/android_td_sdk_release_notes.md): Update time: 2026/05/12 Download
- [iOS](https://docs.thinkingai.io/en/md/integration/ios_td_sdk.md): Latest version: v1.4.1
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/ios_td_sdk_advanced.md): The TDSettings configuration passed in during initialization is described below
- [Release notes](https://docs.thinkingai.io/en/md/integration/ios_td_sdk_release_notes.md): Update time: 2026/05/12 Download
- [Mini programs & mini games](https://docs.thinkingai.io/en/md/integration/minigame_td_sdk.md): Latest version: v1.3.0
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/minigame_td_sdk_advanced.md): The parameters passed in during initialization are described below
- [Release notes](https://docs.thinkingai.io/en/md/integration/minigame_td_sdk_release_notes.md): Update time: 2026/02/02 Download (mini programs) Download (mini games)
- [Unity](https://docs.thinkingai.io/en/md/integration/unity_td_sdk.md): Latest version: v1.3.1
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/unity_td_sdk_advanced.md): The TDSettings configuration passed in during initialization is described below
- [Release notes](https://docs.thinkingai.io/en/md/integration/unity_td_sdk_release_notes.md): Update time: 2025/12/03 Download
- [Unreal](https://docs.thinkingai.io/en/md/integration/unreal_td_sdk.md): Latest version: v1.0.0
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/unreal_td_sdk_advanced.md): The configuration passed in during initialization is described below:
- [Release notes](https://docs.thinkingai.io/en/md/integration/unreal_td_sdk_release_notes.md): Update time: 2025/01/09 Download
- [JS](https://docs.thinkingai.io/en/md/integration/js_td_sdk.md): Latest version: v1.3.0
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/js_td_sdk_advanced.md): The parameters passed in during initialization are described below
- [Release notes](https://docs.thinkingai.io/en/md/integration/js_td_sdk_release_notes.md): Update time: 2026/01/07 Download
- [Flutter](https://docs.thinkingai.io/en/md/integration/flutter_td_sdk.md): Latest version: v1.0.0
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/flutter_td_sdk_advanced.md): The TDStrategySettings configuration passed in during initialization is described below
- [Release notes](https://docs.thinkingai.io/en/md/integration/flutter_td_sdk_release_notes.md): Update time: 2025/12/08
- [HarmonyOS](https://docs.thinkingai.io/en/md/integration/harmony_td_sdk.md): Latest version: v1.0.0
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/harmony_td_sdk_advanced.md): The Strategy SDK is initialized through TDStrategySettings.
- [Release notes](https://docs.thinkingai.io/en/md/integration/harmony_td_sdk_release_notes.md): Update time: 2026/07/24 Download
- [CocosCreator](https://docs.thinkingai.io/en/md/integration/cocoscreator_td_sdk.md): Latest version: v1.4.0
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/cocoscreator_td_sdk_advanced.md): The parameters passed in to TDStrategy.init during initialization are described below
- [Release notes](https://docs.thinkingai.io/en/md/integration/cocoscreator_td_sdk_release_notes.md): Update time: 2026/09/16 Download
- [WeChat subscription message integration guide](https://docs.thinkingai.io/en/md/integration/wechat_subscription_connection.md): This document describes how to report the OpenID of a WeChat mini program to the AE system and bind it to a user property, so that you can push WeChat subscrip…
- [Custom trigger integration guide](https://docs.thinkingai.io/en/md/integration/custom_trigger_access.md): For how to make calls, see the calling method description in the Open API document.
- [KakaoTalk channel push](https://docs.thinkingai.io/en/md/integration/kakaotalk_connection.md): This article describes how to connect Infobip in AE, create a KakaoTalk Brand Message channel, and complete test sends, production pushes, and result troublesh…
- [Experiment SDK integration guide](https://docs.thinkingai.io/en/md/integration/experiment_sdk.md): Experiment
- [Client SDKs](https://docs.thinkingai.io/en/md/integration/experiment_client_sdk.md): Getting configurations on the client relies on the ThinkingData SDK.
- [Android](https://docs.thinkingai.io/en/md/integration/experiment_android_sdk.md): Latest version: v1.0.1
- [Release notes](https://docs.thinkingai.io/en/md/integration/experiment_android_sdk_release_notes.md): Update time: 2026/07/24 Download
- [iOS](https://docs.thinkingai.io/en/md/integration/experiment_ios_sdk.md): Latest version: v1.0.2
- [Release notes](https://docs.thinkingai.io/en/md/integration/experiment_ios_sdk_release_notes.md): Update time: 2026/07/24 Download
- [JS](https://docs.thinkingai.io/en/md/integration/experiment_js_sdk.md): Latest version: v1.0.0
- [Release notes](https://docs.thinkingai.io/en/md/integration/experiment_js_sdk_release_notes.md): Update time: 2026/07/24 Download
- [HarmonyOS](https://docs.thinkingai.io/en/md/integration/experiment_harmony_sdk.md): Latest version: v1.0.0
- [Release notes](https://docs.thinkingai.io/en/md/integration/experiment_harmony_sdk_release_notes.md): Update time: 2026/07/24 Download
- [Unity](https://docs.thinkingai.io/en/md/integration/experiment_unity_sdk.md): Latest version: v1.0.0
- [Release notes](https://docs.thinkingai.io/en/md/integration/experiment_unity_sdk_release_notes.md): Update time: 2026/08/04 Download
- [Server-side SDK](https://docs.thinkingai.io/en/md/integration/experiment_server_sdk.md)
- [Config Center technical integration docs](https://docs.thinkingai.io/en/md/integration/config_integration.md): V4.4 supports two ways to get configurations: via Webhook or via client SDK.
- [Webhook config integration guide](https://docs.thinkingai.io/en/md/integration/config_integration_webhook.md): The Webhook channel of Config Center establishes a connection mechanism for interactive communication with external systems or other internal modules.
- [Client SDK config integration docs](https://docs.thinkingai.io/en/md/integration/config_integration_client.md): Getting configurations on the client relies on the ThinkingData SDK.
- [Android](https://docs.thinkingai.io/en/md/integration/config_integration_android_sdk.md): Latest version: v1.3.0
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/config_integration_android_sdk_advanced.md): The TDSettings configuration passed in during initialization is described below:
- [Release notes](https://docs.thinkingai.io/en/md/integration/config_integration_android_sdk_release_notes.md): Update time: 2026/07/22 Download
- [iOS](https://docs.thinkingai.io/en/md/integration/config_integration_ios_sdk.md): Latest version: v1.3.1
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/config_integration_ios_sdk_advanced.md): The TDSettings configuration passed in during initialization is described below:
- [Release notes](https://docs.thinkingai.io/en/md/integration/config_integration_ios_sdk_release_notes.md): Update time: 2026/07/24 Download
- [Mini programs & mini games](https://docs.thinkingai.io/en/md/integration/config_integration_minigame_sdk.md): Latest version: v1.2.1
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/config_integration_minigame_sdk_advanced.md): The TDSettings configuration passed in during initialization is described below:
- [Release notes](https://docs.thinkingai.io/en/md/integration/config_integration_minigame_sdk_release_notes.md): Update time: 2025/10/30 Download (mini programs) Download (mini games)
- [Unity](https://docs.thinkingai.io/en/md/integration/config_integration_unity_sdk.md): Latest version: v1.2.4
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/config_integration_unity_sdk_advanced.md): The TDSettings configuration passed in during initialization is described below
- [Release notes](https://docs.thinkingai.io/en/md/integration/config_integration_unity_sdk_changelog.md): Update time: 2026/08/14 Download
- [Unreal](https://docs.thinkingai.io/en/md/integration/config_integration_unreal_sdk.md): Latest version: v1.0.0
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/config_integration_unreal_sdk_advanced.md): The configuration passed in during initialization is described below:
- [Release notes](https://docs.thinkingai.io/en/md/integration/config_integration_unreal_sdk_changelog.md): Update time: 2025/01/09 Download
- [JS](https://docs.thinkingai.io/en/md/integration/config_integration_js_sdk.md): Latest version: v1.3.0
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/config_integration_js_sdk_advanced.md): The TDSettings configuration passed in during initialization is described below:
- [Release notes](https://docs.thinkingai.io/en/md/integration/config_integration_js_sdk_changelog.md): Update time: 2026/07/24 Download
- [Flutter](https://docs.thinkingai.io/en/md/integration/config_integration_flutter_sdk.md): Latest version: v1.0.0
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/config_integration_flutter_sdk_advanced.md): The TDRemoteConfigSettings configuration passed in during initialization is described below:
- [Release notes](https://docs.thinkingai.io/en/md/integration/config_integration_flutter_sdk_release_notes.md): Update time: 2025/12/08
- [HarmonyOS](https://docs.thinkingai.io/en/md/integration/config_integration_harmony_sdk.md): Latest version: v1.0.0
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/config_integration_harmony_sdk_advanced.md): HarmonyOS RemoteConfig is initialized through TDRemoteConfigSettings (independent of the initialization configuration of the Analytics SDK).
- [Release notes](https://docs.thinkingai.io/en/md/integration/config_integration_harmony_sdk_release_notes.md): Update time: 2026/07/24 Download
- [CocosCreator](https://docs.thinkingai.io/en/md/integration/config_cocoscreator_sdk.md): Latest version: v1.3.1
- [Advanced guide](https://docs.thinkingai.io/en/md/integration/config_cocoscreator_sdk_advanced.md): Cocos Creator passes in configuration through TDRemoteConfig.init.
- [Release notes](https://docs.thinkingai.io/en/md/integration/config_cocoscreator_sdk_changelog.md): Update time: 2026/9/16 Download