Context.ai, a product analytics platform for LLM-powered applications, launched with $3.5 million in funding co-led by GV (Google Ventures) and Tomasz Tunguz at Theory Ventures.

Chatbots and other natural language products are increasingly integral to how businesses engage with their customers. As any product developer knows, building great user experiences requires visibility into user behavior and understanding of product performance – critical insights that are often lacking for today’s AI applications. Recognizing a void in enterprise-ready analytics solutions, co-founders Henry Scott-Green and Alex Gamble built Context.ai to provide businesses with the product analytics they need to build better AI products.

“It’s hard to build a great product without understanding users and their needs,” said Context.ai Co-Founder and CEO Henry Scott-Green. “Context.ai helps companies understand user behavior and measure product performance, bringing crucial user understanding to developers of LLM-powered products.”

Through Context.ai’s platform, businesses can track frequently discussed conversation topics, identify where their product is performing well versus poorly, debug bad conversations, monitor brand risks, understand user retention, and measure the impact of new releases.

“The current ecosystem of analytics products are built to count clicks. But as businesses add features powered by LLMs, text now becomes a primary interaction method for their users. Making sense of this mountain of unstructured words poses an entirely new technical challenge for businesses keen to understand user behavior. Context.ai offers a solution,” said Context.ai Co-Founder and CTO Alex Gamble.

Companies including Cognosys, Lenny’s Newsletter, and Juicebox rely on Context.ai for product analytics to help them better understand and improve their LLM-powered applications.

Context.ai has achieved SOC2 certification, the gold standard for information security.