Nimble, a New York City-based provider of a real-time web search and data infrastructure platform, has secured $47 million in Series B funding, bringing its total capital raised to $75 million. The round was led by Norwest, with participation from Databricks Ventures and existing investors including Target Global, Square Peg, Hetz Ventures, Slow Ventures, R-Squared Ventures, J-Ventures, and InvestInData.
The fresh funding will be used to accelerate enterprise adoption and expand research into multi-agent web search systems, a rapidly emerging area in artificial intelligence infrastructure.
Building Real-Time Web Data Infrastructure for AI
Founded and led by Uri Knorovich, CEO and Co-Founder, Nimble has developed an enterprise-grade platform designed to convert the public web into structured, decision-ready data for AI systems and mission-critical business workflows.
As AI adoption grows across industries, organizations are increasingly seeking access to live web data to complement internal datasets. Traditional web scraping methods often require complex engineering efforts and compliance management. Nimble aims to simplify this process through a real-time, agentic approach to web search and data extraction.
The company positions itself at the intersection of generative AI, enterprise data platforms, and real-time web intelligence.
Key Components of the Nimble Platform
Nimble’s technology stack includes two primary offerings:
1. Web Search Agents
Nimble provides a no-code AI workflow builder that enables intelligent agents to operate using real web browsers. These agents can navigate websites, extract live data, and stream web-based information directly into enterprise systems.
This capability allows teams to access and integrate real-time web data without heavy engineering overhead. By eliminating the traditional “engineering tax” associated with scraping and browser automation, Nimble reduces the technical barriers to leveraging web-scale intelligence.
2. Web Tools SDK
For developers and technical teams, Nimble offers a Web Tools Software Development Kit (SDK). The SDK provides APIs that allow builders to search, extract, and crawl web data directly from a command-line interface. This enables seamless integration into custom AI applications, data pipelines, and enterprise systems.
The platform is designed to support AI agents that require dynamic, up-to-date information rather than relying solely on static training datasets.
Enterprise AI Integrations with Databricks and Microsoft
Nimble is collaborating with major enterprise technology providers including Databricks and Microsoft. These partnerships are aimed at supporting enterprise AI deployments that require access to both internal corporate data and external real-time web information.
By integrating with established data and cloud ecosystems, Nimble enables enterprises to embed live web data directly into their AI models, analytics environments, and business intelligence systems. This approach supports more accurate decision-making and real-time responsiveness.
The partnerships also signal growing demand for infrastructure that bridges the gap between public web data and enterprise AI workflows.
Growing Demand for Agentic AI and Live Web Data
The rise of agentic AI systems — autonomous AI agents capable of executing tasks and making decisions — has increased the need for reliable, real-time data sources. Many AI models are trained on historical datasets, which can limit their effectiveness in dynamic environments such as market intelligence, competitive analysis, regulatory monitoring, and pricing optimization.
Nimble’s multi-agent web search capabilities are designed to address this challenge by enabling AI systems to access and process live web content. This allows businesses to build AI-driven applications that respond to real-world changes as they happen.
As organizations move beyond experimentation and deploy AI in production environments, demand for scalable, compliant, and real-time data infrastructure continues to rise.
Accelerating Adoption and Research
With the new Series B capital, Nimble plans to scale customer acquisition, enhance product capabilities, and expand research into advanced multi-agent systems. The company is focusing on improving automation efficiency, reducing latency, and enhancing the reliability of web data pipelines.
Investors backing the round reflect confidence in Nimble’s position within the rapidly evolving AI infrastructure ecosystem. The participation of Databricks Ventures underscores the strategic alignment between modern data platforms and real-time AI applications.
Positioning in the AI Infrastructure Market
The AI infrastructure market is becoming increasingly competitive as enterprises seek robust solutions for model training, inference, and real-time decision-making. Nimble differentiates itself by focusing specifically on transforming the public web into structured, enterprise-ready data streams.
By combining browser-based automation, APIs, and no-code tools, Nimble is targeting both technical and non-technical enterprise users. This dual approach allows organizations to deploy AI-driven workflows without extensive engineering resources.
As AI continues to reshape enterprise operations, platforms that enable real-time, agentic access to web data are expected to play a critical role in the next phase of AI deployment.
Conclusion
Nimble’s $47 million Series B funding marks a significant milestone in the evolution of real-time web search infrastructure for AI systems. By bridging the gap between the public web and enterprise AI environments, the company is positioning itself as a key player in the growing agentic AI ecosystem.
With expanded research into multi-agent web search and deeper enterprise integrations, Nimble aims to redefine how organizations access, structure, and operationalize live web intelligence in the age of artificial intelligence.
Ruchi Kumar is the associate editor at Entrepreneur News Network and TVW News India, where she leads editorial strategy, brand storytelling, and startup ecosystem coverage. With a strong focus on innovation, business, and marketing insights, he curates impactful narratives that spotlight India’s evolving entrepreneurial landscape.