New York-based Nimble has secured $47 million in a Series B funding round to expand its real-time web data platform for AI-driven enterprises.
The round was led by Norwest, with participation from returning investors including Target Global, Square Peg, Hetz Ventures, Slow Ventures, R-Squared Ventures, J-Ventures, and InvestInData. Databricks also joined the round. With this financing, Nimble has raised a total of $75 million to date.
Turning Live Web Search Into Structured Enterprise Data
As enterprises increasingly deploy AI agents across workflows, access to reliable, real-time web data has become a growing priority. While large language models can retrieve and analyze information from the web, they often return results in unstructured text formats, which can be difficult to operationalize at scale.
Nimble addresses this challenge by combining AI-powered web search with validation and data structuring capabilities. Its platform retrieves live web data, verifies sources, and transforms results into structured tables that can be queried like traditional databases.
By converting web information into structured datasets, Nimble enables organizations to treat external data as if it were part of their internal systems.
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Integration With Enterprise Data Infrastructure
A core differentiator of Nimble’s approach is its integration with enterprise data warehouses and data lakes, including platforms such as Databricks and Snowflake. This allows AI agents to access both live web information and internal company data within the same environment.
Through these integrations, the system can apply enterprise-defined constraints, such as approved data sources or specific search parameters. This governance layer is designed to reduce risks associated with hallucinations, unreliable sources, or misinterpreted instructions.
Use cases include competitor analysis, pricing intelligence, know-your-customer processes, brand monitoring, financial analysis, and other workflows requiring up-to-date external data.
According to CEO and co-founder Uri Knorovich, the challenge for enterprises is not a lack of AI capabilities but a lack of dependable, structured data. By combining real-time web search with validation and governance, Nimble aims to provide the reliability required for production-grade AI deployments.
Enterprise Adoption And Expansion Plans
Nimble reports more than 100 customers, with the majority of revenue coming from large enterprises, including Fortune 500 and Fortune 10 companies. Clients span industries such as retail, finance, hedge funds, and consumer goods, as well as AI-native startups.
The newly raised capital will be used to expand research and development efforts, particularly in multi-agent web search systems and a governed data layer designed to further improve validation and reliability.
Investor Assaf Harel of Norwest noted that trusted, live web data is becoming essential for AI agents involved in critical business decisions, positioning the company’s infrastructure as increasingly relevant in enterprise AI ecosystems.
About Nimble
Nimble is a New York-based AI infrastructure company providing real-time, validated, and structured web data for enterprise AI systems. By integrating live web search with enterprise data environments, Nimble enables organizations to incorporate trusted external data into production workflows at scale.
