Nimble raises $47 million to give AI agents access to verified, structured web data

Nimble raises $47M to give AI agents access to real-time web data

Believe it or not, web search is still thriving as an industry. As businesses invest in using AI agents to make the most of their data, there's demand for tools that not only scrape the web to inform what those AI bots do, but also return those results in a way that's easier to use with modern data tools. That's the promise behind web search startup Nimble, which recently raised a $47 million Series B round, led by Norwest. The New York company's platform employs AI agents to search the web in real time, verify, and validate the results, and then structure the information into neat tables that can then be queried like a database. That last part is crucial here. LLMs and AI agents are great for searching the web, connecting results from a variety of sources, and analyzing them, but they often return the results in plain text, which can be difficult to work with at an enterprise level. And that's before you factor in hallucinations, the risk of the agent misunderstanding your instructions, or the use of unreliable sources. By validating and structuring results into tables, Nimble lets companies use web data as if it were already part of their existing databases. The startup also integrates with enterprise data warehouses and data lakes -- large centralized repositories where businesses store and analyze data -- offered by the likes of Databricks and Snowflake. That means its AI agents can plug into a business's trove of data, using it to build context, and shape how search results are structured and returned. In effect, this lets enterprises have live, structured web data as part of their existing data environments, Nimble CEO and co-founder Uri Knorovich (pictured above, middle) told TechCrunch. Such integrations also allow Nimble's software to remember constraints -- such as how you want the search to be performed, or which data sources to tap. This is particularly useful for applications such as competitor analysis, pricing research, know-your-customer (KYC) processes, brand monitoring, deep research, and financial analysis. (Knorovich noted that Nimble works to ensure all customer data remains within customers' data infrastructure to comply with data retention and security policies.) To that end, the startup has partnered with Databricks, Snowflake, AWS and Microsoft to help streamline enterprise deployments that require access to internal data sources. (Databricks also participated in this Series B.) "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 said. "What we're seeing today is that enterprises don't need more AI; they need AI with good, reliable web search [...] If you nail it down, if you can choose what your agent can search and cannot search, this is the tipping point for enterprises to say, 'hey we can actually trust AI. We can actually put AI to work in more use cases'." Knorovich says the ability to search the web in real time at scale, and validate and structure search results, is what sets Nimble apart from other data brokers already in the space. The startup currently has more than 100 customers, with the majority of its revenue coming from large enterprises, Fortune 500 companies, and even some Fortune 10 companies, including major retailers, hedge funds, banks, and consumer packaged goods companies, as well as some AI-native startups. "Nimble is tackling a problem that has existed for years without a proper solution and is now becoming of critical urgency," Assaf Harel, partner at Norwest, said in a statement. "Trusted live web data is increasingly becoming a prerequisite for AI agents performing critical business decisions." The Series B also saw participation from returning investors Target Global, Square Peg, Hetz Ventures, Slow Ventures, R-Squared Ventures, J-Ventures, and InvestInData. Proceeds from the round will be used to expand R&D in multi-agent web search and a governed data layer that processes and validates search results. Nimble has now raised a total of $75 million.

Nimble raises $47M to scale agentic web search platform for enterprise AI - SiliconANGLE

Nimble raises $47M to scale agentic web search platform for enterprise AI Nimble announced today that it has raised $47 million in new funding to accelerate development of its agentic web search platform, expand its multi-agent research capabilities and scale up its governed real-time web data infrastructure for enterprise artificial intelligence deployments. Founded in 2021 as Thhe Data Company Technologies Inc., Nimble offers a real-time web search and data platform designed to address the challenge of obtaining structured, verifiable data from the live public internet for use in enterprise AI systems. Many AI deployments rely on static datasets, internal records or unstructured web summaries that are difficult to audit or reproduce. Nimble's approach, on the other hand, centers on coordinating multiple AI-driven agents that browse live websites, extract information and convert dynamic web content into structured, schema-first datasets suitable for operational use in AI deployments. "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 co-founder and Chief Executive Uri Knorovich. "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." Nimble's platform works by using AI models to control full web browsers rather than relying solely on application programming interfaces or static scraping scripts. The agents navigate websites, interact with dynamic page elements, handle changing layouts and retrieve data directly from live sources. Having scraped sites, the platform then applies a governed data layer to process the collected information through steps such as cleaning, deduplication, joining and aggregation. The output is converted into structured tables that can be queried, stored or integrated into enterprise analytics and AI systems. The platform's capabilities include a no-code workflow builder that allows teams to configure browser-based search agents and automate recurring web data tasks and a software development kit provides programmatic access to search, extraction and crawling functions for developers. The system is designed to support long-running, multistep workflows in which one agent gathers information, another cross-checks results, and a governed layer validates outputs before they are delivered into downstream applications. The platform is used in workflows that require timely and verifiable external data, such as financial due diligence, retail pricing analysis, market research, media monitoring and social listening. Nimble's platform also integrates with services from Databricks Inc. and Microsoft Corp. to allow customers to incorporate structured web data into existing data pipelines, business intelligence tools and agent-based applications operating in production environments. The company says Fortune 500 companies use the company's platform to stream trusted web data directly into their workflows. Notable Nimble customers include Databricks, Uber Technologies Inc., The Coca-Cola Co., Tripadvisor Inc., L'Oréal SA, Deloitte Touche Tohmatsu Ltd., Microsoft and LG AI Research. The Series B round was led by Norwest Venture Partners LP, with participation from Databricks Ventures and existing investors including Target Global Management GmbH, Square Peg Capital Pty. Ltd., Hetz Ventures, Slow Ventures, R-Squared Ventures, J-Ventures and InvestInData. "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. "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." The new funding takes the total raised by Nimble to $75 million.