Nimble Raises $47M for Enterprise AI Data Integration
Nimble, a company backed by Databricks, has raised a $47 million Series B round to address the "enterprise AI data gap." The company's platform is designed to integrate messy, real-world data streams from industrial environments into AI training and deployment pipelines for robotics and automation systems.
- The $47 million Series B funding round was led by Norwest, with significant participation from Databricks Ventures and existing investors such as Target Global and Square Peg. This infusion brings Nimble's total capital raised to $75 million. - Nimble was founded in 2021 by CEO Uri Knorovich and CRO Menachem Salinas. The company employs around 120 people, with 70 located in its development center in Israel and the rest at its New York headquarters. - The company's core technology is an "Agentic Search Platform" that deploys coordinated AI agents to navigate the web, including dynamic and JavaScript-heavy sites. These agents extract, verify, and structure live web data into clean, queryable tables, essentially allowing enterprises to treat the web as a structured database. - This funding aims to address the challenge of AI systems requiring reliable, up-to-date external information, a problem that traditional web scraping and legacy data vendors have struggled to solve without high costs and fragility. Many AI failures in production environments stem from poor data quality rather than the models themselves. - The investment from Databricks is strategic, enabling deeper integration with the Databricks Data Intelligence Platform. This allows customers to merge Nimble's real-time external web data with their own internal datasets within their existing data environments. - Nimble plans to use the new capital to scale its browser automation infrastructure and advance its research in multi-agent systems and governance layers to ensure data correctness and auditability for high-stakes enterprise decisions.
