DataBahn Raises $40M to Build an Agentic Control Layer for Enterprise Data

Funding DataBahn Raises $40M to Build an Agentic Control Layer for Enterprise Data Published July 30, 2026 By Antoine Tardif, CEO & Founder of Unite.AI Add Unite.AI to your preferred sources on Google DataBahn has raised $40 million in Series B funding as it looks to expand the infrastructure enterprises use to prepare, govern and deliver data to artificial intelligence systems.Insight Partners led the round, with existing investors Forgepoint Capital, GTM Capital and S3 Ventures also participating. The investment brings the Dallas-based company’s total funding to $59 million, following a $17 million Series A announced in June 2025.DataBahn plans to direct the new capital towards research and development, additional product capabilities and the continued expansion of its partner-led sales model. The company is positioning its platform as an “agentic data control plane,” an infrastructure layer intended to manage how enterprise data moves between operational systems, security platforms, storage environments and AI models.The round comes as businesses are generating more telemetry than their existing security and analytics systems can economically process. At the same time, AI agents and copilots require access to reliable enterprise context if they are expected to make useful decisions or take actions on behalf of employees.Moving Beyond Conventional Data PipelinesTraditional enterprise data pipelines generally collect information from a source and deliver it to a destination, such as a security information and event management platform, data warehouse or cloud storage system.That model becomes less effective as the number of data sources, destinations and consumers expands. An enterprise may need to collect logs from cloud infrastructure, identity systems, endpoints, applications, industrial equipment and software-as-a-service platforms, while simultaneously sending different portions of that information to security tools, analytics systems, data lakes and AI applications.Moving every available event into every downstream system can create substantial storage, processing and cloud data-transfer costs. It can also make it more difficult for analysts and AI models to locate the information that is genuinely relevant.DataBahn inserts a management layer between those sources and destinations. Its platform can collect, filter, normalize, enrich and route information while it is moving, rather than requiring each downstream application to independently process the raw data.The company says its technology currently supports more than 600 data sources and is designed to remain independent of any particular storage platform, security vendor or AI model. This allows customers to change destinations or use several systems without rebuilding the collection layer around each vendor’s architecture.DataBahn initially focused heavily on cybersecurity telemetry but has since expanded its platform to cover application, observability and Internet of Things and operational technology data.Preparing Enterprise Data for AI AgentsThe AI component of DataBahn’s strategy is not limited to adding a conversational interface to an existing data platform.Its Cruz AI system functions as an agentic data engineer that assists with work traditionally