Israeli startup Nimble raises $47M Series B led by Norwest, backed by Databricks Ventures, to deliver verified real-time web data for enterprise AI.
An Israeli startup betting that artificial intelligence is only as strong as the data beneath it has secured $47 million in new funding to expand its real-time web intelligence platform.
Nimble, which develops an agent-based system for live web search and enterprise-grade data verification, announced a Series B round led by Norwest Venture Partners, with participation from Databricks Ventures and existing investors including Square Peg, Target Global, Hetz Ventures, Slow Ventures, R-Squared Ventures, J-Ventures and InvestInData.
The round brings the company’s total funding to $75 million.
Founded in 2021 by Chief Executive Uri Knorovich and Chief Revenue Officer Menachem Salinas, Nimble employs roughly 120 people — about 70 at its development center in Israel and the remainder at its New York headquarters.
“We have been building Nimble quietly for four years. Now it’s our time to step into the spotlight,” Mr. Knorovich said. He previously co-founded Cyronix, a cybersecurity company that was sold before Nimble’s launch.
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Search, Rebuilt for Enterprises
Nimble argues that while consumer search engines excel at broad discovery, enterprise AI systems require something more rigorous: structured, verified and continuously updated data streams that can withstand regulatory and operational scrutiny.
“Agents are capable of doing many things, but business search at the level of accuracy organizations need hasn’t existed,” Mr. Knorovich said. “Google serves consumers well, but companies require specialized, reliable search systems.”
The company’s platform deploys AI agents that browse the web through real browsers and APIs, extract and verify information, then clean and structure the data into organized tables. The result is enterprise-ready datasets designed for high-stakes applications such as due diligence, dynamic pricing, market research and risk analysis.
A Strategic Bet by Databricks
The participation of Databricks Ventures underscores a broader industry push to integrate external, real-time web intelligence with internal enterprise data lakes.
According to Nimble, its system enables companies to run search and retrieval workflows directly within their Databricks environments, keeping sensitive data internal while enriching it with live web information. The startup also collaborates with Microsoft to integrate real-time web data into enterprise ecosystems without relying on fragile third-party scraping tools.
“Agents are becoming the new interface for the Internet,” Mr. Knorovich said. “Our platform grows in value as more users leverage it.”
Competing — and Complementing — AI Labs
Despite operating in a landscape shaped by powerful AI models such as Claude, Nimble positions itself not as a competitor but as infrastructure.
The company says it collaborates with major AI labs to strengthen the search layer beneath automated reasoning systems. While large language models may generate insights or decisions, Nimble focuses on ensuring that the underlying data is verifiable and current.
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Trust, executives argue, is the differentiator.
As enterprises accelerate AI adoption, failures often stem not from model capability but from incomplete, outdated or unverifiable data. Nimble’s pitch is straightforward: if AI is to move from experimentation to mission-critical deployment, the data pipeline must be as intelligent as the models it feeds.
The company now serves hundreds of clients, including LG, Deloitte, Uber, L’Oréal, Coca-Cola and Tripadvisor — organizations where precision and timeliness are not optional.
In an AI economy increasingly defined by scale, Nimble is wagering that the next competitive edge will not be a larger model, but cleaner, live and defensible data.
