Keenable.ai

Keenable.ai is a research-driven AI infrastructure company building an independent web search platform specifically for AI agents and large-scale AI applications. Founded in 2025 by Andrey Styskin and Matthias Petri, the company aims to solve the bottlenecks AI models face when accessing live web data. The founders bring extensive experience in developing large-scale search infrastructure; Styskin previously served as CEO of Yandex Search and a director at Amazon AGI, while Petri was a Principal Applied Scientist at Amazon AGI. Their shared background includes building web-scale search systems at both Yandex and Amazon.

The company addresses the limitations of traditional search engines, which are designed for human interaction and are economically and technically inefficient for the high-frequency, low-latency query patterns of AI agents. Keenable's platform is built around its own independent web index of over 100 billion documents, designed to make web access an order of magnitude more cost-efficient for AI systems. This enables AI applications to continuously retrieve fresh information from the web without incurring prohibitive costs or latency.

Keenable provides its service to AI labs, inference platforms, and researchers through a suite of products including a low-latency Search API, a Fetcher API for retrieving clean, model-ready content, and a 'Time Machine' feature that allows searches across historical snapshots of the web. The company is also developing a 'Web Query Language for AI,' designed to let models retrieve and synthesize information from thousands of sources. Its business model includes a pay-as-you-go tier for developers and a dedicated capacity tier for large-scale enterprise clients, with pricing based on API request volume. Having emerged from stealth with $26 million in seed funding led by Accel, Keenable has already secured contracts with multiple AI labs.

Keywords: AI search API, agentic economy, web search for AI, knowledge access, large language models, retrieval primitives, independent web index, AI infrastructure, low-latency search, content retrieval, Andrey Styskin, Matthias Petri, search for agents, retrieval systems, web crawling, AI data access, AI model training, real-time web data, autonomous agents, API for AI, AI developer tools, machine-readable web