Search engines were designed for humans, who lack the time and attention to scan entire webpages. But with the growing reliance on AI chatbots for search and task completion, a compelling case has emerged for re-architecting internet infrastructure to serve AI, which can process vastly larger amounts of information.
Andrey Styskin, former head of search, AI, and cloud at Russian tech giant Yandex, and German AI scientist Matthias Petri are tackling this challenge with their startup, Keenable. The company recently emerged from stealth with $26 million in seed funding, led by Accel and joined by Conviction Partners and several business angels.
From Styskin's perspective, AI chatbots perform significantly better when they can ground their responses in source documents. "This creates a new flywheel, different from what Google learned from human behavior," he told TechCrunch.
Keenable claims to have built a web search index of over 100 billion documents, with its API already in production at several AI labs and inference providers during both training and runtime. While the startup hasn't disclosed its customers, it recently announced a partnership with voice AI company Gradium to support real-time information retrieval.
Drawing on 20 years of search experience at Yandex and Amazon, Styskin explained how Keenable's approach differs from enterprise search solutions, which can become prohibitively expensive at web scale. "If you don't fine-tune your index structures for a specific task, the cost of serving and scanning the entire internet is enormous because of the volume. That's why you need to innovate on narrowing the search space based on your query very quickly. That's what we bring to the table," he said.
Accel partner Zhenya Loginov, who led the investment, noted that AI players have limited options for web-scale search infrastructure. This is particularly true as Google and Microsoft move to shut down their existing search APIs to avoid cannibalization. Instead, the tech giants are leaning toward bundled offerings and selective partnerships.
These industry shifts validated the opportunity Styskin identified while at Amazon, where he and Petri worked on web search infrastructure for AI applications like Alexa. He cited Cloudflare data showing AI crawlers accounting for a growing share of search volume, reinforcing the need for AI-native web search infrastructure.
Leveraging his network, Styskin assembled a team of former colleagues for Keenable, which is also developing proprietary retrieval capabilities. This includes an upcoming product, WebQueryLanguage, designed to help AI systems answer questions by combining information from multiple web sources, even when no single source contains the full answer.
Cost remains a critical factor. Styskin acknowledges that moving users away from Google is "extremely hard," but the innovator's dilemma suggests the U.S. giant may be vulnerable on agentic queries. A lean, specialized player like Keenable could carve out a niche in this emerging space.
via TechCrunch AI