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

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 res...