Global data volumes have grown by nearly 182% between 2020 and 2025, and an estimated 80% of that data remains unstructured. Now, as AI agents and systems move from experimentation to production, this number will only continue to grow exponentially.
But we still fail to realize the value from the largest source of data out there: the web. In an era of highly fragmented and fast-growing web data, AI developers require trusted search solutions to build accurate and dependable systems. Most data engineering teams try to close this gap with a mix of search APIs, custom scraping pipelines, and third-party data providers. Each approach solves part of the problem, but none address it end-to-end. Making this data available to non-human AI workflow elevates the challenge exponentially.
We’ve followed Nimble over several years as its talented team worked through these challenges firsthand. Their focus has remained consistent on making real-time web search accurate, particularly for enterprise organizations that must make immediate business decisions at scale. Today, we are happy to share that Norwest led Nimble’s $47 million Series B.
Why Reliable Web Data Matters Now
As AI agents assume greater responsibility across functions, from dynamic pricing and forecasting to regulatory compliance, the integrity and reliability of the underlying data are now mission‑critical, while doing this at enterprise scale.
Most existing approaches break down under these conditions:
- Real-time. Data vendors offer coverage, but often struggle to keep data fresh or adaptable.
- Accuracy. Search APIs return quick answers, but the data comes in large text blocks that are difficult for agents to decipher.
- Overhead. Scraping pipelines fail as websites constantly change, forcing expensive data teams to focus on ongoing maintenance rather than invest time in business innovation.
Not to mention, the operational cost is significant with data preparation and validation accounting for 50 to 80% of the time spent on AI and analytics projects. When web data is inconsistent, teams spend more time fixing inputs than building systems that create value — a problem grows exponentially with scale. Solving this requires a system that can operate reliably at scale.
A CEO with a Clear Vision
No one understood how complex web data can be or how much effort it takes to keep it usable better than Nimble’s co-founders, CEO Uri Knorovich and CRO Menachem Salinas. As such, Nimble founders have been on Norwest’s radar since the company’s early days. That long-standing relationship allowed us to track the team progress and the business over multiple years before ultimately deciding to invest.
At Norwest, we often look for founders who have deep domain expertise informed by years of exposure to the problem they’re trying to solve. Uri embodies that principle with years of working across AI and large-scale data systems. Instead of building for a quick trend, he focused on the underlying constraint.
Nimble’s Agentic Web Search Platform: A Production-Grade Infrastructure Layer
Nimble is the first company to build a platform that makes live web data reliable, scalable, and enterprise-grade ready so that data teams, business users and, now, non-human agents can operate continuously in ever-changing, real-world environments, focusing on innovation and building use cases rather than chase and maintain data.
The company is working closely with Databricks and Microsoft to support enterprise AI deployments that require access to real-time web data alongside internal data sources. These partnerships enable enterprises to integrate the live web directly into their existing data and AI environments.
Nimble is also partnering with leading AI labs to bring frontier models out of demos and into production-grade, browser-based systems. With multiple models in the backend, Nimble transforms state-of-the-art AI research into dependable Web Search Agents that enterprises can trust to run continuously in mission-critical environments.
“With multiple models in the backend, Nimble transforms state-of-the-art AI research into reliable Web Search Agents that enterprises can trust to run continuously in mission-critical environments.”
Why Customers Choose Nimble
Through our diligence, we went deep on the technology and consistently heard strong feedback from multiple stakeholders on Nimble’s ability to deliver reliable, high-quality web data at enterprise scale. That feedback has been validated time and again by customers like Drata.
One global on-demand food delivery marketplace evaluated 17 alternatives before selecting Nimble, underscoring both the criticality of the problem and lack of adequate solutions in the market. Similarly, a Fortune 50 global beverage manufacturer with operations in 200+ countries has used Nimble to monitor large volumes of marketplace data across channels. For most of its customers, Nimble unlocks business needs that could not be met using traditional solutions or data engineering.
For us, these customer outcomes solidified our conviction in the company and belief that as AI moves into mission-critical workflows, reliable web data becomes foundational.
What Reliable Data Means for the Next Generation of AI Applications
Nimble’s team brings deep expertise across AI, data infrastructure and web technologies, with a clear understanding of both the technical complexity of large-scale web data systems and the operational demands of enterprise AI.
The next generation of AI will not be defined by model size alone, but by the reliability of the data beneath it. As AI systems take on responsibility in high-stakes environments such as healthcare, fintech and government agencies, trust depends on accuracy, completeness and control. Organizations must know that their agents are working from live, high-fidelity data and that they can see and shape how it is gathered.
Nimble has been building the missing layer between the open web and enterprise AI. As agents move from experiments to mission-critical workflows, the companies that win will not just have the biggest models, but the most reliable data. That is the future that Nimble is building towards.
