Your AI Agent Can't Google Things. A $26M Startup Is Fixing That.
Last week I asked one of my AI agents to research a prospect's company before a call. The agent hit Google's rate limit after twelve queries, stalled for thirty seconds, then returned garbage results scraped from a page designed for human eyeballs.
That's the problem with the current agent boom. We're building AI systems that can reason, plan, and execute multi-step workflows. Then we hand them a search engine built in 1998 for people typing three words into a box.
A startup called Keenable thinks that's absurd. They just emerged from stealth with $26 million in seed funding led by Accel, with angel investors from Google and Amazon backing the round.
What they actually built
Keenable has indexed over 100 billion documents and built a search API from scratch for AI agents. Not a wrapper on top of Google. Not a Bing API with a rate limit prayer. A retrieval system designed from the ground up for the way agents actually work.
Their stack includes low-latency search, page-content retrieval, and an MCP interface with both cloud and dedicated-capacity options. The company was founded in 2025 by Andrey Styskin and Matthias Petri. They've got a 15-person team across the US and Europe, and they plan to double headcount by the end of 2026.
Why this matters if you run agents
If you've built AI agents that need to pull information from the web, you've probably hit the same walls I have. Google and Bing charge per query, throttle aggressively, and return HTML pages stuffed with ads and JavaScript that your agent has to parse.
That's like handing a forklift operator a shopping cart.
Keenable's approach skips all of that. Their API returns clean, structured data at the speed agents need. No rate limit roulette. No scraping headaches. No praying that the page renders correctly in a headless browser.
The bigger picture for business owners
This fits a pattern I keep seeing in 2026. The flashy consumer AI apps grabbed all the attention in 2024 and 2025. Now the real money is moving into infrastructure. The boring plumbing that makes AI agents actually reliable.
Think about what happened with the early internet. The first wave was websites. The second wave was the stuff that made those websites fast, secure, and able to handle growth. CDNs, cloud hosting, payment processing. The companies that built that layer became some of the most valuable in tech.
AI is following the same path. We've got the agents. Now we need the picks and shovels.
What to do about it
If you're running AI agents in your business today, or planning to, keep three things in mind.
First, watch the infrastructure layer. Tools like Keenable, agent-specific browsers like Cloudflare's Kitesurf, and dedicated compute platforms are all signs that the agent stack is maturing fast.
Second, budget for search. If your agents need web access, "free Google results" isn't a real strategy. Factor in API costs for agent-grade search the same way you budget for model API calls.
Third, test your agent workflows under load. Most agent search failures happen at scale, not during demos. The prospect research that works for one lead breaks when you try to run fifty at the same time.
The $26 million bet is really about timing. AI agents are about to become the primary consumers of web information, and the infrastructure hasn't caught up. From what I'm seeing with my own clients, Keenable is right about the gap. Whether they're the ones who fill it is a different question. But the problem is real, and it's costing businesses time and reliability right now.
— Mark Garza, Laimen AI
