The web used to be a library. Now it is a street fight. Every second, pages change, data mutates, signals blur. Most enterprises are still screenshotting the chaos and calling it strategy.

Nimble just raised $47M in Series B funding to step into that noise and make it usable. Norwest led the round. Databricks Ventures stepped in. Target Global, Square Peg, Hetz Ventures, Slow Ventures, R-Squared Ventures, J-Ventures, and InvestInData doubled down. Total funding now sits at $75M. Not hype capital. Infrastructure capital.

Credit where it is due. Uriel Knorovich, Co-founder & CEO, built this company in 2021 with a clear thesis. The live web is not a content problem. It is a data problem. And most AI systems are starving not because they lack models, but because they lack clean, real-time external data to think with.

Nimble runs Web Search Agents that move through the internet with intent. They search, extract, clean, aggregate, and structure. They turn messy pages into decision-grade data. For enterprises running AI agents, analytics engines, and go-to-market systems, that difference is not cosmetic. It is existential.

Look at the proof. Grips Intelligence uses Nimble for large-scale e-commerce pricing and product data. Qodo powers AI-driven code review on structured web intelligence. Alta runs millions of AI-driven GTM workflows per day on top of Nimble’s feeds. That is not a slide deck. That is load-bearing production.

Databricks Ventures joining the round is not a casual check. It signals alignment between the modern data stack and the live web. Internal data tells you who you were. External web data tells you what is happening now. When those streams converge inside platforms like Databricks, AI stops guessing and starts operating.

Nimble is Israeli-founded, headquartered in New York, and positioned right in the blast radius where AI meets infrastructure. No vanity metrics disclosed. No valuation theater. Just a focused build on agentic web search and enterprise-grade reliability.

The business lesson is simple but not easy. They did not chase every shiny AI demo. They solved the plumbing. They made the web queryable, structured, and AI-ready. Investors followed the traction. Customers validated the need. The market rewarded clarity.

In a world obsessed with model benchmarks, Nimble is betting on the pipes. And if AI is going to run real workflows across commerce, software, and sales, somebody has to own the live data layer.

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