Athina AI

What is Athina AI?

Athina AI is a platform for building, testing, and managing AI applications powered by large language models (LLMs). It provides a collaborative, spreadsheet-like editor for prototyping ideas, experimenting with different approaches, evaluating performance, and monitoring live AI products.

The platform is an end-to-end solution for AI application development. It includes enterprise-grade security controls, on-premises deployment options, role-based access controls, multiple workspaces, access to custom models from providers like Azure OpenAI and AWS Bedrock, and flexible pricing for teams of different sizes.

Who created Athina AI?

Shiv Pratap Singh founded Athina AI. The platform handles millions of requests every week for various teams. Industry leaders including Michael Brady from RightPage and Eshan Agarwal from Epsilon AI have praised its impact on AI product development.

What is Athina AI used for?

• Access management: Role-based access controls ensure the right people have access to the right features and data.
• Building and testing: Prototype new AI features, experiment with different applications, and evaluate LLM-powered apps.
• Monitoring and evaluation: Track LLM outputs and test AI products quickly to catch issues.
• Advanced testing scenarios:
  • Rerun prompts across multiple models to compare performance.
  • Test different models against the same data trace.
  • Regenerate datasets using different models or prompts.
  • Transform data with dynamic columns for flexible analysis.
  • Compare prompts side-by-side to refine effectiveness.
  • Compare datasets using a diff view to spot differences.
• End-to-end development: Use the collaborative, spreadsheet-like editor to experiment, prototype, and test AI products at speed.
• Deployment flexibility: Self-hosted deployment keeps data private within your own cloud.

Who is Athina AI for?

Athina AI is built for anyone involved in AI development, including AI developers, data scientists, product managers, AI researchers, data engineers, machine learning engineers, and software engineers.