Keenable launches with $26M for agentic search

Keenable's launch comes from a clear pain point: existing web search was built for humans, but AI agents need low-latency, high-frequency queries. Co-founder Andrey Styskin realized this during his time at Amazon, where he worked with Petri on web search for Alexa. The startup's independent index of over 100 billion documents is designed to handle these queries efficiently, avoiding the high cost of scanning the entire internet.

The team's background in search—Styskin at Yandex and Petri at Amazon AGI—lends credibility to the technical approach. Keenable also introduces Web Query Language, which helps AI systems draw from multiple sources to answer questions even when no single source has the full answer. This could be significant for complex queries.

With $26 million in funding, Keenable plans to double its headcount, signaling intent to scale quickly. The market opportunity is large: most AI agents still use traditional search APIs or build their own crawlers. Keenable's dedicated index could offer a competitive edge, but it faces rivals like Tavily, Exa, and Perplexity, which it claims to outperform in relevant, clean information delivery.