DataBahn Raises $40 Million for Agentic Data Control Plane

DataBahn announced a $40 million Series B on July 30 led by Insight Partners, with Forgepoint, GTM Capital and S3 Ventures participating, bringing total funding to $59 million. The company plans to expand its agentic data control plane, which ingests, normalizes and routes enterprise telemetry from more than 600 sources, and reported over 400% year-over-year revenue growth with no customer churn.

DataBahn Raises $40 Million for Agentic Data Control Plane DataBahn announced a $40 million Series B on July 30 led by Insight Partners, with Forgepoint, GTM Capital and S3 Ventures participating. The company said the round brings total funding to $59 million and will expand its agentic data control plane; SiliconANGLE reports that the platform ingests, normalizes and routes enterprise telemetry from more than 600 sources. DataBahn announced a $40 million Series B on July 30 to expand its agentic data control plane. Insight Partners led the round, with existing investors Forgepoint, GTM Capital and S3 Ventures participating. The company said the financing brings its total funding to $59 million . DataBahn plans to use the capital for research, development and product innovation, extending the platform from large global enterprises into the mid-market. A control layer for enterprise telemetry DataBahn sells software that sits between systems generating telemetry and the tools that consume it. SiliconANGLE reports that the platform ingests, normalizes and routes data from more than 600 sources , reducing and enriching information in transit before sending it to security platforms, data warehouses, analytics tools or AI systems. The company’s pitch is that AI agents and copilots need governed enterprise context rather than unfiltered log streams. Its platform is designed to route only the data required for real-time operations while retrieving additional context on demand, with no required lock-in to a particular destination or AI model. DataBahn also reported more than 400% year-over-year revenue growth, 180% net revenue retention, no customer churn and a 97% proof-of-concept win rate. Those figures come from the company and were not independently verified in the retrieved coverage. SiliconANGLE reports that customers include Fortune 100 organizations in healthcare, financial services, manufacturing and transportation. Implications for data and ML teams The funding reflects a broader infrastructure problem: AI applications increase demand for context-rich operational data while raw telemetry volumes raise storage, transfer and inference costs. Filtering, normalizing and enriching data before it reaches a model can reduce unnecessary context volume and improve consistency. That architecture also creates a consequential control point. Teams evaluating this approach should validate lineage, access controls, retention rules, failure handling and the quality of transformations applied in transit. They should also test whether volume reduction preserves the signals needed by downstream detection and analytics systems rather than relying only on vendor-reported savings or growth metrics. Key Points - 1DataBahn announced a $40 million Series B led by Insight Partners, bringing company-reported total funding to $59 million. - 2SiliconANGLE reports that the platform processes telemetry from more than 600 sources and routes governed context to enterprise applications and AI systems. - 3The company’s growth and customer-performance figures are self-reported; teams still need to validate lineage, access controls and downstream signal preservation. Scoring Rationale The $40 million Series B is a notable enterprise-data infrastructure event tied to telemetry routing and context preparation for AI applications. It matters to data and ML teams managing governance and cost, though the vendor’s growth and performance figures remain company-reported. Sources Primary source and supporting public references used for this report. Practice interview problems based on real data 1,625 SQL & Python problems across 15 industry datasets — the exact type of data you work with. Try 250 free problems /problems