Measure & Improve LLM Product Performance.
Before & After Launch.

Context.ai gives you confidence in the performance of your LLM products, with pre-launch evaluations and post-launch analytics.

Trusted By
Build LLM Products with Comprehensive
Performance Monitoring
Start with pre-launch evaluation to build confidence in your application

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.

Continue with product analytics to track performance with real users

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

Demo Video
Evaluations
Establish and maintain quality in your LLM powered products
Create test cases of representative LLM inputs

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.

Evaluate quality on the criteria that matter to you

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.

Perform rigorous comparison across iterations

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.

Analytics
Understand and improve user experiences in production
1. Ingest Transcripts to Context.ai in less than 30 minutes

Integrate with Context.ai using our SDKs, or send transcripts directly via our API.

Our SDKs make it easy to get started.

2. Group Conversations by Topic

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.

3. Pinpoint and Resolve Poor Experiences

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.

Enterprise
Trust and Security for Enterprise
SOC 2 Compliant
Context.ai is SOC 2 Type II compliant, so you can have confidence your data is handled with the highest levels of security.
Self-Hosted Deployment
Context.ai offers a self-hosted option for customers with the strictest data residency requirements.
Hear From Our Customers

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.

Rod Smyth
CEO & Co-Founder at Glyde Talent

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.

Matthew Phillips
CEO & Co-Founder at Superflows

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.

Sully Omar
CEO & Co-Founder at Cognosys
Measure & Improve LLM Product Performance.
Before & After Launch.