Web search remains a robust industry as businesses focus on utilizing AI agents to maximize their data potential. There’s a growing need for tools that scrape the web to support AI functions and present results in formats compatible with modern data technologies.
Nimble, a web search startup, has tapped into this demand, securing a $47 million Series B funding round led by Norwest. The New York-based company’s platform leverages AI agents to conduct real-time web searches, verify information, and organize it into structured tables that function like databases.
The ability to provide structured data is a significant advantage. While LLMs and AI agents excel at web searches and synthesizing data from various sources, they often deliver results in plain text, posing challenges at the enterprise level. Moreover, issues such as hallucinations, misinterpretations, or unreliable sources can complicate matters.
Nimble addresses these challenges by validating and organizing results in table formats, allowing companies to seamlessly integrate web data with their existing databases. The startup’s solution also works with enterprise data warehouses and data lakes — centralized hubs for data storage and analysis provided by companies like Databricks and Snowflake. This integration enables Nimble’s AI agents to access extensive data repositories, shaping search result structures.
This capability integrates real-time, structured web data into existing enterprise environments, explained Nimble CEO and co-founder Uri Knorovich.
Such functionalities enable Nimble’s software to retain search constraints, optimizing applications such as competitor analysis, pricing research, customer profiling, brand monitoring, in-depth research, and financial analysis. Knorovich emphasized that Nimble ensures customer data remains within their infrastructure in compliance with security policies.
To enhance enterprise deployment involving internal data access, partnerships with Databricks, Snowflake, AWS, and Microsoft have been established. Databricks also contributed to this Series B round.
“AI models have vast potential, but AI failures often stem from data issues, not model inadequacies,” Knorovich stated. “Enterprises need reliable web search-enhanced AI. When an organization knows what its AI can and can’t access, it truly starts to trust and implement AI in more use cases.”
Nimble’s capability to perform scalable, real-time web searches, validating and structuring the results, differentiates it from existing data brokers.
Currently, the startup boasts over 100 clients, with most revenue deriving from large enterprises — including Fortune 500 and Fortune 10 companies, spanning sectors like retail, finance, and consumer goods, alongside AI-native startups.
“Nimble is tackling an age-old issue that now demands urgent solutions,” Norwest partner Assaf Harel commented. “Reliable live web data is crucial for AI agents tasked with essential business decisions.”
Returning investors such as Target Global, Square Peg, Hetz Ventures, Slow Ventures, R-Squared Ventures, J-Ventures, and InvestInData also participated in this Series B. The funding will enhance R&D in multi-agent web search and establish a governed data layer for processing and validating search results.
To date, Nimble has raised a total of $75 million.