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Keenable addresses a critical infrastructure gap for AI agents by providing a specialized web index optimized for machine consumption rather than human browsing efficiency. By leveraging advanced indexing techniques to narrow search spaces at scale, the startup aims to reduce the computational costs associated with training and running large language models on the open internet. This approach represents a significant shift in how AI systems retrieve and ground information from unstructured web data.
Accel-backed Keenable is indexing the web for AI agents
Now exiting stealth mode with a $26 million seed round, Keenable has been building a vast web search index for AI agents.
Search engines were built and optimized for people, who can’t spare the time or attention required to scan entire webpages. But as people increasingly use AI chatbots to search the web and do tasks, there’s a line of thinking that the Internet’s current infrastructure needs to be updated to cater to AI instead, as these bots can read and process much larger portions of information. Andrey Styskin, who previously led Russian search giant Yandex’s search, AI and cloud division, and German AI scientist Matthias…
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