Make sure your LLM application is prepared for whatever users throw at it.
Comprehensively test your LLM and measure it for accuracy, bias, and more.
Understand and improve how LLMs are being used in your product, with pre-launch evaluations and post-launch analytics.
Make sure your LLM application is prepared for whatever users throw at it.
Comprehensively test your LLM and measure it for accuracy, bias, and more.
Monitor how your product performs with real people, and understand how they're using it.
Real user data is the ultimate test of success, and tells you where you can improve your product
Experiment with ideas in the playground, then migrate to test sets for more rigorous evaluation.
Context.ai supports LLMs from all major providers including OpenAI, Anthropic, Google, and Meta.
Run hundreds of simulated user queries and assess the generated responses using LLMs, custom code, golden responses, or manual ratings.
Use our pre-built evaluators, or build your own.
Compare across versions and test cases to understand how performance is changing over time.
Integrate prompts against your CI/CD pipeline to automatically run your full test suite on every PR.
Integrate with Context.ai using our SDKs, or send transcripts directly via our API.
Our SDKs make it easy to get started.
With Context.ai, you can automatically group conversations by keyword, or by related words and topics.
We'll also suggest relevant groups of conversations too, helping you uncover hidden behavior patterns.
Deep dive into conversation transcripts to understand exactly where users are having good, great, or poor experiences.
Search and filter by user ratings and sentiment to understand how you can improve their experiences.
The challenge that the scale of AI chat brings is understanding which needle to look for in the haystack.
Context.ai immediately gave me what I needed: Data that I could use to close more sales and insights for engineering to improve the user experience.
Context.ai gives us confidence that changes will perform well before we ship them to production, and then shows their performance with real users - this is incredibly helpful.
We struggled to gain meaningful insights from the large amounts of data generated by our platform. It was difficult to understand exactly how users were interacting with the system and what they were trying to accomplish.
With Context.ai, we are able to derive more insights into how users interact with our product. This has been huge for understanding our users better, so we can focus on the areas that matter.