Nimble secures $47M to power AI agents with live web data access

Believe it or not, web search is still very much alive as an industry. And as more businesses invest in AI agents to extract value from their data, there’s growing demand for tools that can scrape the internet to inform what those agents do — and then deliver those findings in a format that fits modern enterprise data workflows.

That’s the bet behind web search startup Nimble, which has raised a $47 million Series B round led by Norwest. The New York-based company says its platform uses AI agents to search the web in real time, verify and validate what it finds, and then structure that information into clean tables that can be queried like a database.

That final step is central to Nimble’s pitch. LLMs and AI agents can be useful for browsing the web, connecting information across sources, and analysing results, but they often return answers as plain text. At enterprise scale, that kind of output can be difficult to operationalise — even before considering the risk of hallucinations, the agent misunderstanding instructions, or pulling from questionable sources.

By validating and converting results into structured tables, Nimble aims to make web data usable in the same way companies use their internal databases. The startup also plugs into enterprise data warehouses and data lakes — the centralised repositories where organisations store and analyse large volumes of data — via integrations with platforms from companies such as Databricks and Snowflake. These connections allow Nimble’s agents to work alongside a company’s internal data, using it to build context and to influence how web search outputs are formatted and returned.

In practice, this means enterprises can treat live web data as part of their existing data environments, CEO and co-founder Uri Knorovich said.

Those integrations also help Nimble maintain search constraints over time — such as how a search should be run, what rules should apply, and which sources to include or exclude. Knorovich said this is especially useful for competitor analysis, pricing research, know-your-customer (KYC) processes, brand monitoring, deep research, and financial analysis. He also noted that Nimble works to keep customer data within the customer’s own data infrastructure to align with data retention and security requirements.

To support deployments that require access to internal data sources, Nimble has partnered with Databricks, Snowflake, AWS, and Microsoft. Databricks also participated in this Series B round.

“Models can do a lot of things, but most production AI fails aren’t because the models are not good enough — it’s because of a data failure,” Knorovich said. “What we’re seeing today is that enterprises don’t need more AI; they need AI with good, reliable web search … If you nail it down, if you can choose what your agent can search and cannot search, this is the tipping point for enterprises to say, ‘Hey, we can actually trust AI. We can actually put AI to work in more use cases.”

Knorovich argues that Nimble’s ability to run real-time web search at scale — while validating and structuring the output — is what separates it from other data brokers operating in the same space.

Nimble says it now has more than 100 customers, with most of its revenue coming from large enterprises — including Fortune 500 and even some Fortune 10 companies. Its customers include major retailers, hedge funds, banks, consumer packaged goods companies, and several AI-native startups.

“Nimble is tackling a problem that has existed for years without a proper solution and is now becoming of critical urgency,” Assaf Harel, a partner at Norwest, said in a statement. “Trusted live web data is increasingly becoming a prerequisite for AI agents performing critical business decisions.”

The Series B round also included participation from returning investors Target Global, Square Peg, Hetz Ventures, Slow Ventures, R-Squared Ventures, J-Ventures, and InvestInData. Nimble said the new funding will be used to expand R&D into multi-agent web search and to build a governed data layer that processes and validates search results.

With this raise, Nimble says it has now brought in $75 million in total funding.