Nimble Launches Agentic Search Platform with $47M Series B, Aims to Transform Web Search for AI with 99% Accuracy
Nimble has announced the launch of its Agentic Search Platform, a system designed to convert the public web into reliable, decision-grade data for AI systems and business workflows. This launch is backed by a $47 million Series B funding round led by Norwest, with participation from Databricks Ventures, bringing Nimble's total funding to $75 million. The platform addresses the challenge of LLMs often reasoning over incomplete or unverifiable external information by providing a governed data layer that searches, navigates, and validates live internet data in real time. Nimble's co-founder and CEO, Uri Knorovich, highlighted his long-held vision of a machine-centric internet, which is now being validated by current AI adoption. The platform utilizes a proprietary distributed architecture with specialized agents to perform tasks typically handled by humans or web scrapers, aiming for 99% accuracy.
Web search has already seen significant disruption from AI, as evidenced by Google's AI Overviews, Bing's integration of OpenAI's GPT models, and Perplexity's AI-driven web search platform. Building on this trend, Nimble has officially launched its Agentic Search Platform. This innovative system is engineered to transform the vast public web into trusted, decision-grade data specifically for AI systems and various business workflows. The launch is significantly bolstered by a successful Series B financing round, securing $47 million. This round was led by Norwest, with additional investment from Databricks Ventures and other participants, elevating the company's total funding to an impressive $75 million.
Nimble's initiative directly confronts a critical bottleneck prevalent in the current AI landscape. While large language models (LLMs) are continuously advancing in sophistication, they frequently encounter limitations due to reasoning over external information that is either incomplete or lacks verifiable sources. The Agentic Search Platform aims to bridge this "guesswork gap" by establishing a governed data layer. This layer is designed to search, navigate, and validate live internet data in real time, ensuring the information provided to AI systems is accurate and reliable.
In an exclusive interview with VentureBeat, Nimble's co-founder and CEO, Uri Knorovich, reflected on the initial skepticism he faced regarding his vision for a machine-centric internet. Knorovich recounted, "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 acknowledged that these early assertions were often deemed "too visionary." However, the rapid and widespread adoption of AI in recent times has unequivocally validated his foundational thesis.
The core technological innovation behind Nimble’s solution lies in its proprietary distributed architecture. This architecture is designed to orchestrate a network of specialized agents. These agents are tasked with performing functions that have traditionally been the domain of human researchers or often-fragile web scrapers. According to the company's infrastructure documentation, this intricate process is systematically broken down into five distinct layers, beginning with a headless browser and browsing agent.