Keenable raises $26M to build a web search index for AI agents

Andrey Styskin, who previously led Russian search giant Yandex’s search, AI, and cloud division, and German AI scientist Matthias Petri are building Keenable, a startup working on web-search infrastructure designed for AI systems rather than people. The company recently came out of stealth with $26 million in seed funding, led by Accel, with participation from Conviction Partners and some business angels.

Styskin argues AI chatbots perform better when they can ground responses in source documents, calling it “a new flywheel that is different from what Google learned from human behavior.” Keenable says it has built a web search index of more than 100 billion documents, and its API is already used in production at several AI labs and inference providers during both training and runtime. The startup wouldn’t disclose its customers but said it recently struck a partnership with voice AI company Gradium to support live information retrieval.

Drawing on 20 years building search at Yandex and Amazon, Styskin said Keenable differs from enterprise search products that get costly at web scale: narrowing the search space for a specific task, rather than scanning the whole internet on every query, is what keeps serving costs manageable.

Accel partner Zhenya Loginov, who led the investment, said AI companies have few options for web-scale search infrastructure, especially as Google and Microsoft move to shut down existing search APIs to avoid cannibalizing their own products, opting instead for bundled, selective partnerships. Styskin said Cloudflare data showing AI crawlers taking a growing share of search volume confirmed an opportunity he’d already spotted while building search infrastructure for Alexa at Amazon.

Keenable, which has a team of 15 engineering staff across the U.S. and Europe, plans to use the new funding to double headcount by year-end and build out its go-to-market effort. It is also developing an upcoming product, Web Query Language, meant to help AI systems answer questions by combining information from multiple web sources even when none contains the full answer alone.

Styskin acknowledged that convincing people to abandon Google search is “extremely hard,” but argued the search giant is “beatable” on agentic queries, where a smaller, cost-efficient challenger like Keenable sees an opening. Competitors including Brave and Exa have also entered the space, and Google itself is overhauling its search experience for the AI era.

Why it matters

As Google and Microsoft restrict access to their search APIs, AI labs have few independent options for grounding chatbot responses in web data — an opening Keenable is betting it can fill before Google adapts its own search product for agents.