Keenable provides web search and data retrieval infrastructure purpose-built for AI agents and large language models. Its SELECT tool lets models query the web as a structured database, returning tables and distributions instead of ranked links, enabling more accurate and evidence-grounded responses. The company operates a large independent web index with low-latency APIs designed for high-scale AI workloads.
Funding
Funding not disclosed
Founders
Product
Problem
AI agents and large language models struggle to access web knowledge effectively using traditional search APIs, which return human-oriented "10 blue links" and snippets. These tools are expensive, slow, and force models to query sparingly, limiting their ability to ground answers in up-to-date, real-world evidence. As a result, models often rely on parametric memory, producing generic or outdated responses instead of leveraging the vast, growing body of public information.
Solution
Keenable provides web search infrastructure specifically designed for AI labs and inference platforms, enabling models to access web knowledge cheaply and at scale. The company has built one of the largest independent web indexes in the world, offering a Search API with sub-250ms p95 latency. Its flagship tool, SELECT, allows agents to query the web as a database using SQL-like syntax, transforming unstructured pages into structured tables and distributions—such as aggregating pricing data across competitor sites—rather than returning individual documents. This approach shifts the model's task from keyword matching to analytical querying, giving it the whole picture instead of isolated snippets.
Target Audience
Primary customers are AI labs, inference platforms, and large-scale AI application builders that need reliable, low-cost web access for agentic workflows and retrieval-augmented generation.
Features
- Search API with sub-250ms p95 latency (US East) and capacity for 100+ requests per second
- SELECT tool that treats the web as a dataframe, supporting filter, group, aggregate, count, and column extraction operations
- Index of 100B+ documents, built as an independent alternative to major search engines
- Cloud and on-premises deployment options for dedicated capacity
- Time Machine feature for accessing historical web snapshots
- SQL-like query syntax that nudges models to request comprehensive datasets rather than single answers