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

Believe it or not, the web search industry is still booming. As companies increasingly deploy AI agents to leverage their data, there's a growing need for tools that do more than just scrape the web to inform these AI bots. Businesses want tools that deliver search results in a format that's easier to integrate with modern data systems.

This is the core mission of web search startup Nimble, which just secured a $47 million Series B funding round led by Norwest. The New York-based company's platform uses AI agents to conduct real-time web searches, verify the findings, and then neatly structure the information into queryable tables, much like a database.

That final step is key. While large language models and AI agents excel at scouring the web, synthesizing information from multiple sources, and performing analysis, they often output results as plain text. This format can be cumbersome for enterprise-scale operations. This challenge is compounded by issues like AI hallucinations, the risk of the agent misinterpreting instructions, or reliance on untrustworthy sources.

By validating information and organizing it into structured tables, Nimble enables companies to treat web data as if it were natively part of their own databases. The startup also integrates with major enterprise data warehouses and data lakes—such as those from Databricks and Snowflake—which are centralized repositories for business data storage and analysis. This allows Nimble's AI agents to connect with a company's internal data troves, using that context to refine how search results are structured and delivered.

In essence, this gives enterprises access to live, structured web data within their existing data environments, Nimble CEO and co-founder Uri Knorovich explained to TechCrunch.

These integrations also enable Nimble's software to retain specific constraints, such as preferred search methodologies or approved data sources. This capability is especially valuable for tasks like competitor analysis, pricing research, know-your-customer (KYC) checks, brand monitoring, in-depth research, and financial analysis. (Knorovich emphasized that Nimble ensures all customer data stays within the customer's own infrastructure to meet data retention and security policies.)

To facilitate this, the startup has established partnerships with Databricks, Snowflake, AWS, and Microsoft to simplify deployments that require access to internal data sources. (Databricks also joined as an investor in this Series B round.)

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“AI models are capable of many things, but most production AI failures stem from data issues, not from inadequate models,” stated Knorovich. “What we're observing is that enterprises don't necessarily need more AI; they need AI powered by reliable, high-quality web search [...] If you can precisely control what your agent can and cannot search, it becomes a tipping point. Companies can then confidently say, 'We can actually trust AI and deploy it across more use cases.'”

According to Knorovich, Nimble's differentiation lies in its ability to perform real-time web searches at scale, while also validating and structuring the results—a combination that sets it apart from other data brokers in the market.

The startup currently serves over 100 customers, with the bulk of its revenue derived from large enterprises, including Fortune 500 and even some Fortune 10 companies. Its client base spans major retailers, hedge funds, banks, consumer packaged goods firms, and several AI-native startups.

“Nimble is addressing a long-standing problem that lacked a proper solution and has now reached a critical level of urgency,” said Assaf Harel, a partner at Norwest, in a statement. “Trusted, live web data is increasingly essential for AI agents that are involved in critical business decision-making.”

The Series B round included participation from returning investors Target Global, Square Peg, Hetz Ventures, Slow Ventures, R-Squared Ventures, J-Ventures, and InvestInData. The new capital will be used to expand research and development in multi-agent web search and a governed data layer responsible for processing and validating search results.

To date, Nimble has raised a total of $75 million.