Nimble, a real-time web search and data platform focused on turning the live web into reliable, decision-grade data for enterprises, has raised $47 million in Series B financing, bringing its total funding to $75 million. The round was led by Norwest, with participation from Databricks Ventures and all existing investors, including Target Global, Square Peg, Hetz Ventures, Slow Ventures, R-Squared Ventures, J-Ventures, and InvestInData.
The company said the funding will accelerate product innovation and expand its agentic search capabilities, supported by a broader ecosystem that includes Microsoft and Databricks to help bring trusted live web data into production AI systems.
Nimble positions itself as distinct from traditional consumer search engines and AI summarization tools by focusing on enterprise-grade, verifiable, and structured data. While many AI systems generate text-based answers that may lack reproducibility, Nimble is designed to automate web browsing and convert live internet data into curated, AI-ready tables for mission-critical use cases such as retail pricing intelligence, financial due diligence, and bank-grade market research.
The company said teams that require high accuracy are often forced to rely on service vendors or maintenance-heavy scraping solutions, creating a gap between AI’s promise and real-world outcomes. Nimble’s Agentic Search Platform uses coordinated agents to navigate the web and a governed data layer to process, analyze, cross-check, and structure results into schema-first tables that can be queried like a database.
According to the company, Fortune 500 enterprises use Nimble to stream trusted web data directly into their workflows, replacing legacy data vendors and traditional scraping approaches. The platform includes Web Search Agents, a no-code AI workflow builder that uses real browsers to navigate websites and stream live data, and a Web Tools SDK that provides APIs for developers to search, extract, and crawl the web without managing scraping infrastructure.
Nimble is also working with Databricks and Microsoft to support enterprise AI deployments that require access to real-time web data alongside internal data sources. Through integrations such as Delta Sharing support with Databricks and connections to Microsoft’s enterprise AI environments, the company aims to help organizations operationalize AI systems that depend on up-to-date external data.
Headquartered in New York, Nimble works with leading AI labs and leverages models from OpenAI, Anthropic, and open-source innovations from Meta to power multimodal, browser-based agents. Rather than generating summaries, the company uses these models to control real browsers, navigate dynamic websites, cross-check results, and produce auditable data outputs for long-running workflows in high-stakes environments.
KEY QUOTES
“The greatest source of intelligence for businesses and AI is the web, but the data is dynamic and hard to verify, which is why we built Nimble. Businesses already run multi-agent systems where one agent searches, another verifies results from the web, and a third takes action, and Nimble’s agentic search powers that loop with verified data from the web. We automate millions of actions per day, saving customers tens of millions of dollars annually and driving measurable topline impact. We are doing for business what traditional web search did for consumers, but with correctness, completeness, and control as first-class requirements. Getting reliable web data shouldn’t be that hard.”
Uri Knorovich, CEO And Co-Founder Of Nimble
“Nimble is tackling a problem that has existed for years without a proper solution and is now becoming of critical urgency. Trusted live web data is increasingly becoming a prerequisite for AI agents performing critical business decisions. As enterprises deploy AI in high-stakes environments, the need for trusted, clean, governed, live web data becomes essential.”
Assaf Harel, Partner At Norwest
“Pricing information used to take weeks to review and turn into strategy. Nimble creates the organizational capability to respond to competitor price changes in minutes; not just by delivering data, but by putting that control in the hands of an agent and the business.”
Julie Averill, Former Chief Information Officer At Lululemon
“At Databricks, we’re focused on helping organizations get real, measurable value from AI. Achieving that requires operationalizing AI with data that goes beyond internal systems. Nimble complements the Databricks Data Intelligence Platform with Delta Sharing support and provides a real-time web data layer, helping customers extend their data and AI workflows beyond internal sources and into the live web.”
Andrew Ferguson, Vice President Of Databricks Ventures
“As enterprises deploy AI agents into real business workflows, access to trusted, real-time web data becomes a foundational requirement. Nimble’s approach of turning the live web into governed, decision-grade data helps organizations move AI from experimentation into production with confidence.”
Atanu Ghosh, Sr. Director Of Agentic Co-Innovation At Microsoft
