Athina AI is a powerful platform designed to help developers monitor and evaluate Language Model Models (LLMs) in production. With Athina, developers can gain complete visibility into their RAG pipeline and utilize over 40 preset evaluation metrics to detect hallucinations and measure performance.
One of the key features of Athina AI is its ability to automatically detect and fix hallucinations in LLM outputs. By analyzing the outputs for hallucinations, misinformation, quality issues, and other bad outputs, developers can ensure the accuracy and quality of their LLMs. Athina AI allows for easy configuration for any LLM use case, making it a versatile tool for developers working with different models and prompts.
In addition to monitoring and detecting hallucinations, Athina AI also provides developers with tools for debugging their RAG pipeline. With the ability to search, sort, and filter through inference calls, developers can trace through queries, retrievals, prompts, responses, and feedback metrics to identify and debug generation issues.
Athina AI offers conversational insights, allowing developers to explore conversations, understand user sentiments, and learn which conversations may have ended poorly. By comparing performance metrics across different models and prompts, developers can identify the best-performing model for each specific use case.
To get started with Athina AI, developers can easily integrate the platform into their existing codebase with just a few lines of code. Athina AI offers a self-hosted solution for complete privacy and control, as well as a GraphQL API for programmatic access to logs and evaluations. The platform also provides cost optimization options, prompt management features, multiple user support for collaboration, and historical analytics to track model performance over time.
To learn more about Athina AI and its features, visit their website here.