Nimble raises $47 million Series B backed by Databricks to close enterprise AI data gaps
The Israeli startup’s platform automates real-time web data collection, verification, and integration for businesses worldwide.
Nimble, a startup developing an agent-based real-time web search and data platform, has raised $47 million in a Series B round, bringing its total funding to $75 million. The round was led by Norwest Fund, with participation from Databricks Ventures and existing investors including Square Peg, Target Global, Hetz Ventures, Slow Ventures, R-Squared Ventures, J-Ventures, and InvestInData.
Founded in 2021 by Uri Knorovich (CEO) and Menachem Salinas (CRO), Nimble employs roughly 120 people, 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,” Knorovich told Calcalist. “We previously sold Cyronix, a cybersecurity company, and I realized that at Nimble, we were creating something bigger. We built a strong infrastructure to solve one of the biggest gaps in enterprise search. Agents are capable of doing many things, but business search at the level of accuracy organizations need hasn’t existed. Google serves consumers well, but companies require specialized, reliable search systems.”
One notable investor is Databricks. Knorovich explains, “Databricks invested because our platform allows enterprises to integrate search directly into their Databricks environment, keeping data internal. Nimble enables real-time information retrieval from the web to inform business decisions. Agents are becoming the new interface for the Internet, and our platform grows in value as more users leverage it.”
Despite competition from AI giants such as Claude, Nimble positions itself as complementary and trustworthy. “We collaborate with major labs, including Claude and Cursor, to produce excellent search infrastructure. While Claude automates decision-making, the search layer is ours. Trust is a key differentiator, our clients rely on us for verified, dependable information.”
The need for reliable data is growing as enterprises increasingly deploy AI-based systems. Many AI models fail when trained on partial, outdated, or unverifiable data, leaving companies frustrated and limiting AI’s real-world business value.
Nimble’s platform turns the vast amounts of Internet data into structured, reliable information for enterprise AI systems. AI agents automate web browsing via real browsers and APIs, navigate websites, extract information, and verify its accuracy. Data is then cleaned, de-duplicated, and converted into organized tables that businesses can safely use in critical decision-making.
The startup currently serves hundreds of companies where accuracy is essential, including LG, Deloitte, Uber, L’Oréal, Coca-Cola, and Tripadvisor. Clients use Nimble for real-time due diligence, dynamic pricing, rapid market research, media strategy optimization, and analyzing online discourse.
Nimble collaborates with Databricks and Microsoft to integrate real-time web data with internal datasets, eliminating reliance on external scraping solutions that are difficult to maintain and often unreliable.
