Athina AI

What is Athina AI?

Athina is a collaborative AI development platform designed for teams to build, test, and monitor AI features. It enables both non-technical and technical users to collaborate on experiments, evaluate datasets, manage prompts, and flows. With Athina, you can compare datasets side-by-side and interact with them using SQL, while building complex AI flows without engineering complexity. The platform is built for human QA teams to work alongside AI evaluations, supporting both programmatic access for engineers and a user-friendly UI for non-technical users.

Key features include native LLM tracing that captures every step of your flows, allowing you to replay and debug issues. Online evaluations can be configured to run on logs in real-time, providing continuous visibility into accuracy. Analytics are segmented at every level, enabling comparisons by prompt, model, topic, or customer ID. Athina ensures full data privacy with fine-grained access controls and deployment in your own VPC, complying with SOC-2 Type 2 standards. It also supports custom models and providers like Azure OpenAI and AWS Bedrock.

Benefits include improved collaboration between teams, faster iteration from prototyping to production, and comprehensive monitoring. Use cases range from initial prototyping to refining models and monitoring performance in production. Athina is ideal for organizations that need a robust, privacy-compliant platform for managing the entire AI lifecycle, from development to deployment. Technical details include SQL-based dataset interaction, API integration, and customizable evaluation metrics. The platform is designed to scale with your needs, providing tools for logging, evaluation, and analytics in one unified interface.

Use Cases

Key Features

collaborative AI development LLM tracing online evaluations real time monitoring side by side dataset comparison SQL interaction prompt management flow building fine grained access controls VPC deployment

Who is it for?

AI developers, QA teams, product managers, data scientists, non, technical collaborators, DevOps engineers, platform teams

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