AI Documentation Overview
The AI Documentation feature provides standardized documentation for all AI capabilities within Teammately. This system automatically generates consistent documentation for each AI Agent, enabling users to quickly understand capabilities and integration options without struggling through inconsistent formats. We recommend to share this documentation with your project's collaborators.
Documentation Structure​
The documentation begins with a Summary section that offers a concise overview of the AI's purpose, core functionality, and key benefits. This helps users quickly determine if the AI meets their needs by explaining how it processes data and the value it delivers.
Following the summary, the Major Use Cases section outlines the primary intended applications, giving concrete examples of how the AI can be utilized in real-world scenarios. This helps users envision practical implementations in their own workflows.
The Milestones section provides transparency about the development and deployment status, including information about completion dates, deployment status, and any relevant technical achievements.
Under AI Architecture & Logic Plans, users gain insight into the technical design of the AI, including the underlying model structure, processing flow, and logical decision-making approach. This section is particularly valuable for technical stakeholders who need to understand how the AI functions at a deeper level.
The documentation clearly specifies API Input/Output Keys to show exactly what data the AI expects and what it returns. This is complemented by a Steps section that breaks down the AI's processing workflow into distinct stages, explaining the transformation from raw input to structured output.
Evaluation and Performance​
The Quick Test Results section provides example inputs and outputs that serve as verification points, allowing users to understand expected behavior through concrete examples.
More comprehensive performance data appears in the Evaluation Results section, which presents detailed metrics and assessment reports. This includes information about the AI's accuracy, consistency, and effectiveness across different use cases, providing transparency about strengths and limitations.
Integration Support​
The Integration section explains how to access the AI via API, complete with code examples in multiple programming languages. This practical guidance includes authentication methods, endpoint details, and proper request formation. The documentation also provides OpenAPI specifications for standardized integration.
To help users visualize implementation possibilities, Frontend Examples showcase sample UI implementations that demonstrate how the AI can be incorporated into user-facing applications.
Finally, the Future Improvements section outlines the development roadmap, highlighting planned enhancements and potential feature additions. This gives users insight into the AI's evolution and helps them plan for future capabilities.
This comprehensive documentation approach ensures that all Teammately AI capabilities are presented with consistent, high-quality information, enabling developers to quickly implement AI features in their applications with confidence.