Nimble, a startup that provides real-time web search and data services for enterprises, said it has raised $47 million in Series B funding, bringing its total capital raised to $75 million, as companies seek more reliable data to power AI systems in high-stakes business environments.
The round was led by Norwest, with participation from Databricks Ventures and existing investors including Target Global, Square Peg, Hetz Ventures, Slow Ventures, R-Squared Ventures, J-Ventures and InvestInData.
Nimble says its platform is used by hundreds of enterprises and is designed to supply verified, real-time web data to production AI systems. The company said the new funding will be used to expand its technology and scale its platform, supported by partnerships with Microsoft and Databricks aimed at integrating live web data into enterprise AI environments.
“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,” said Uri Knorovich, the company’s co-founder and chief executive. He said many organizations now operate multi-agent AI systems in which one agent searches the web, another verifies results and a third takes action, and that Nimble’s technology is designed to support that loop with verified data. The company says it automates millions of actions per day and saves customers tens of millions of dollars annually.
Unlike consumer-focused search engines such as Google, which are built to help users navigate links, or AI tools that summarize text-based answers, Nimble says it focuses on delivering granular, enterprise-grade data for real-time decision-making. Its system uses AI to automate web browsing and convert live internet data into curated, structured tables that can be accessed by AI agents. Use cases include retail pricing intelligence and financial market research.
“Where there is no room for mistakes, we choose Nimble,” said Lior Solomon, vice president of data at Drata, a customer.
The company says many enterprises that require high levels of accuracy have historically relied on service vendors or maintenance-heavy web scraping tools. It argues that AI-generated answers often lack verifiability and reproducibility, creating a gap between AI’s potential and measurable business outcomes.
Nimble said the new funding will accelerate development of its Agentic Search Platform, which supports coordinated AI agents navigating the web and a governed data layer that processes, analyzes and cross-checks information step by step. The platform turns live web data into structured, schema-based tables that can be queried like a database, the company said.
“Nimble is tackling a problem that has existed for years without a proper solution and is now becoming of critical urgency,” said Assaf Harel, a partner at Norwest. He said trusted live web data is increasingly required as enterprises deploy AI in critical decision-making processes.
The platform supports workflows such as financial due diligence, e-commerce pricing analysis, media strategy optimization, social listening and other research tasks where data accuracy and freshness are essential.
Nimble says it processes web data at scale — cleaning, joining, deduplicating, aggregating and governing it — so companies can feed reliable datasets into business intelligence systems and AI agents, rather than relying on web snippets or high-level summaries.
“Pricing information used to take weeks to review and turn into strategy,” said Julie Averill, former chief information officer at Lululemon. “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.”
Nimble is working with Databricks and Microsoft to integrate real-time web data into enterprise data and AI systems. Through Delta Sharing support and integration with the Databricks Data Intelligence Platform, customers can incorporate external web data alongside internal data sources, the companies said.
“At Databricks, we’re focused on helping organizations get real, measurable value from AI,” said Andrew Ferguson, vice president of Databricks Ventures. He said extending AI workflows beyond internal systems to the live web is increasingly important.
Through its Microsoft integration, Nimble enables organizations to embed real-time web data into analytics, research and AI workflows within business applications. Atanu Ghosh, senior director of agentic co-innovation at Microsoft, said access to trusted, real-time web data is becoming foundational as enterprises move AI agents from experimentation into production.
Nimble also said it works with leading AI labs to operationalize advanced models in browser-based systems. Rather than using models solely to generate summaries, the company uses multimodal and reasoning capabilities to control real browsers, navigate dynamic websites, cross-check results and produce auditable outputs over long-running workflows. It integrates models from OpenAI and Anthropic, along with open-source innovations from Meta, to create web search agents designed for continuous use in mission-critical environments.