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 Petri are working to solve that problem with their new startup, Keenable. The company recently came out of stealth $26 million in seed funding. Accel led the funding round, which also saw participation from Conviction Partners and some business angels.
From Styskin’s perspective, AI chatbots tend to do much better if they can ground their responses with source documents. “This actually creates a new flywheel that is different from what Google learned from human behavior,” he told TechCrunch.
Keenable says it has been building 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 who its customers are, but it recently struck a partnership with voice AI company Gradium to support live information retrieval.
Drawing from his experience of 20 years building search at Yandex and Amazon, Styskin explained how Keenable’s product is different from enterprise search solutions that can break down and prove very costly at web scale. “If you do not fine-tune your index structures for a specific task, the cost of serving and scanning the whole internet is enormous because of the volume. That’s why you need to innovate on how you can narrow the search space based on your query very fast. This is what we are bringing to the table,” he said.
According to Accel partner Zhenya Loginov, who led the investment, AI players have very few options when it comes to web-scale search infrastructure, especially with Google and Microsoft taking steps to shut down their existing search APIs to avoid cannibalization. Instead, the tech giants are opting for a more bundled approach, and being selective about their partners.
To Styskin, these decisions confirmed the opportunity he saw when he was at Amazon, working with Petri on web search infrastructure for AI applications such as Alexa. He’d seen Cloudflare data that AI crawlers were responsible for a growing share of search volume, and started realizing that there was an opportunity to develop web search infrastructure that is built with AI in mind.
Armed with that experience, Styskin tapped into his network to hire a handful of former colleagues for his new startup, which is also building proprietary retrieval capabilities. This includes an upcoming product, WebQueryLanguage, which would help AI systems answer questions by combining information from various web sources, even when none contain the full answer.
Costs will be an important part of the equation. Styskin says while it is “extremely hard” to convince people to move away from Google for search, the innovators’ dilemma means that the U.S. giant is potentially “beatable” on agentic queries, and a smaller company like Keenable can innovate and offer a more cost-efficient solution to AI companies.
Still, the costs of building a giant search index are real. “Don’t ask — it is painfully expensive,” he said. But, he says the startup is doing its best to keep costs in check and pace itself. With a team of 15 engineering staff across the U.S. and Europe, the company plans to use the fresh cash to double its headcount by the end of the year to build its go-to-market motion.
There are many more steps before the startup can achieve its dream of becoming “the next Google for AI agents.” Other players have entered the space, such as Brave and Exa; and Google itself is overhauling its search experience for the AI era. But this broader motion indicates that Keenable’s conviction is also shared at the Googleplex: whether it’s for humans or for agents, the era of the “ten blue links” may be coming to a close.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.
Anna Heim is a writer and editorial consultant.
You can contact or verify outreach from Anna by emailing annatechcrunch [at] gmail.com.
As a freelance reporter at TechCrunch since 2021, she has covered a large range of startup-related topics including AI, fintech & insurtech, SaaS & pricing, and global venture capital trends.
As of May 2025, her reporting for TechCrunch focuses on Europe’s most interesting startup stories.
Anna has moderated panels and conducted onstage interviews at industry events of all sizes, including major tech conferences such as TechCrunch Disrupt, 4YFN, South Summit, TNW Conference, VivaTech, and many more.
A former LATAM & Media Editor at The Next Web, startup founder and Sciences Po Paris alum, she’s fluent in multiple languages, including French, English, Spanish and Brazilian Portuguese.
In less than 48 hours, your chance to save up to $300 on your tickets will end!
Two years after launch, Walmart’s Flipkart is closing in on India’s quick-commerce leaders
Inherent, founded by DeepMind alumni, says its AI ‘teammate’ just outperformed Anthropic and OpenAI at replicating research
Michael Polansky is training an AI model on skin that’s still alive
How AI accounting startup Rillet raised $100M and became a unicorn in 48 hours
Tesla’s solar roof is dead — here’s what went wrong
Oura faces lawsuit accusing it of misleading consumers about sleep-tracking accuracy
Home batteries are suddenly cheap and everywhere. Here’s why.






