Keenable.ai’s cover photo
Keenable.ai

Keenable.ai

Technology, Information and Internet

San Francisco, California 1,085 followers

Building the search engine for AI Agents

About us

Keenable.ai is building the next Google for AI Agents — the essential layer that connects AI agents to world knowledge and in future to each other, powering the $1T agentic economy

Website
https://keenable.ai
Industry
Technology, Information and Internet
Company size
11-50 employees
Headquarters
San Francisco, California
Type
Privately Held
Founded
2025

Locations

Employees at Keenable.ai

Updates

  • View organization page for Keenable.ai

    1,085 followers

    We are looking for a founding GTM hire to join the Keenable team. Remote: US, Bay Area preferred. The job sits between the engineering team and our customers, so you will: - talk to the researchers and ML engineers who evaluate web search at AI labs and inference platforms, - build the demo inside their own agent or eval harness and show the result on their queries, not ours, - run evals and pilots to a verdict, closing the deal yourself when the terms are standard, and - own integrations with inference platforms and agent frameworks, and the funnel that turns their usage into accounts. In August we came out of stealth with $26M led by Accel, with Conviction. We have an independent index of more than 100 billion documents, purpose-built for AI agents. Now we’re growing the team behind it.

    • No alternative text description for this image
  • Ask your agent how many researchers Anthropic hired from other labs this year. You'll probably get a number and no idea where it came from. Keenable SELECT answers questions whose answer isn't printed on any page: it reads over a thousand pages in one run, keeps a row for everything it finds, and computes the answer from those rows. Every row keeps its source, so you can check where the answer came from.

    • No alternative text description for this image
  • Keenable Search is now native to Baseten. You turn on hosted web search and page fetch in your Baseten request, Baseten runs the tool and passes the retrieved content back to the model. The model searches, reads, and keeps reasoning inside that same request. No separate search API key and agent loop to manage now. We want models to search more: to check an assumption instead of guessing, and to follow a lead before answering. Baseten is our first inference-platform partner, and context management, quality, and latency are what we'll keep working on.

    • No alternative text description for this image
  • We're hiring at Keenable - Member of Technical Staff: Rust, remote worldwide - Head of Product: founding role, remote in the US - Head of Revenue: founding role, San Francisco In August we came out of stealth with $26M led by Accel, with Conviction. We have an independent index of more than 100 billion documents, built for AI labs and agents. Now we're growing the team behind it. Know the right person? Tag them in the comments, or send them straight to the form

    • No alternative text description for this image
  • Agents still search through ten blue links. We wrote down what they should get instead. Our answer: a SQL-like query in, a table over a slice of the web out. New essay, a gallery of examples, and free through September.

    Agents still search through ten blue links. We wrote down what they could get instead. With Keenable SELECT, agents can get structured data from the internet on the fly. In the article, we explain when snippets are not enough and show how agents can use Keenable SELECT to retrieve distributions of data points and reason over them—not just individual search results. It works through SQL-like queries and gives agents structured dataframes they can compute over directly. Search shouldn’t just return links or snippets. It should give agents data they can compute and reason over.

Similar pages