Nimble Raises $47M to Give AI Agents Access to Real-Time, Verified Web Data

Nimble Secures $47 Million Series B Funding to Transform Web Data for AI Agents

Nimble announced it has raised $47 million Series B funding led by Norwest Venture Partners, with participation from Databricks Ventures and existing investors including Target Global, Square Peg, Hetz Ventures, Slow Ventures, R-Squared Ventures, J-Ventures, and InvestInData 1

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. The New York-based startup has now raised a total of $75 million since its founding in 2021 1

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. The company's agentic web search platform addresses a fundamental challenge facing enterprise AI deployments: accessing real-time web data that is both verifiable and structured enough to support critical business decisions.

Solving the Data Quality Bottleneck for Enterprise AI Deployments

While LLMs and AI agents excel at searching the web and analyzing information from multiple sources, they typically return results in plain text that proves difficult to work with at enterprise scale 1

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. Uri Knorovich, co-founder and CEO of Nimble, emphasizes that most production AI failures stem not from inadequate models but from data failures. "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 told TechCrunch 1

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The platform delivers structured web data with greater than 99% accuracy and latency of 1-2 milliseconds per request 2

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Multi-Agent Systems Power Verifiable Data for AI

Nimble's platform employs a proprietary distributed architecture that orchestrates specialized agents through five distinct layers: headless browser and browsing agents, parsing agents, data processing agents, and validation agents 2

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. Unlike standard web scrapers, these multi-agent systems use AI models to control full web browsers, navigating dynamic layouts and cross-checking results to produce auditable data outputs 3

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The platform validates and structures search results into neat tables that can be queried like a database, allowing companies to use web data as if it were already part of their existing databases 1

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Integration with Data Infrastructure Enables Live Internet Data Access

Nimble integrates with enterprise data warehouses and data lakes offered by Databricks and Snowflake, along with partnerships with AWS and Microsoft 1

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. This allows the platform's AI agents to plug into a business's existing data infrastructure, using internal data to build context and shape how search results are structured and returned. Knorovich noted that Nimble works to ensure all customer data remains within customers' data infrastructure to comply with data retention and security policies 1

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. The governed data layer processes and validates search results, transforming the public web into decision-grade data for AI systems and business workflows 2

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Fortune 500 Adoption Signals Enterprise Readiness

The startup currently serves more than 100 customers, with the majority of revenue coming from large enterprises, Fortune 500 companies, and even some Fortune 10 companies 1

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. Notable customers include Databricks, Uber, Coca-Cola, Tripadvisor, L'Oréal, Deloitte, Microsoft, and LG AI Research, spanning major retailers, hedge funds, banks, and consumer packaged goods companies 3

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. The platform supports use cases such as competitor analysis, pricing intelligence, KYC processes, brand monitoring, market research, due diligence, and financial analysis 1

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Machines as First Citizens of the Web

Knorovich's vision centers on a fundamental shift in how the internet is accessed. "Whenever we started this company, and the first time I went to investors, I told them the web is built for humans, but machines are going to be the first citizens of the web," he recalled 2

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. The scale of AI interaction with the web differs dramatically from human behavior. While humans search for three to five options before making decisions, Nimble performs more than 3.2 million interactions with the web every day 2

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. This programmatic shift requires new infrastructure designed specifically for machine-scale operations.

Investment Signals Critical Urgency for Trusted Web Data

Assaf Harel, partner at Norwest, emphasized the timing of the investment: "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" 3

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. Proceeds from the Series B will be used to expand R&D in multi-agent web search and the governed data layer that processes and validates search results 1

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. As enterprises deploy AI in high-stakes environments requiring multi-million dollar decisions, the need for clean, governed, verifiable data becomes essential for building trust in AI systems.