DataBahn Raises $40 Million Series B Led by Insight Partners to Accelerate Innovation Across the Agentic Data Control Plane

With demonstrated enterprise demand and a partner-led sales model, DataBahn will invest in R&D and new product capabilities that turn data in motion into intelligence in action 

DALLAS, July 30, 2026DataBahn today announced the closing of a $40 million Series B funding round led by Insight Partners, with participation from existing investors Forgepoint, GTM Capital and S3 Ventures. The round brings the company’s total funding to $59 million.

The funding comes as enterprises face a fundamental shift in how their data is consumed. Security platforms, data warehouses and analytics tools are no longer the only systems that depend on enterprise telemetry. AI agents, copilots and autonomous applications increasingly require trusted, contextualized data to reason, make decisions and take action. 

At the same time, organizations are confronting rapidly rising costs associated with collecting, moving, storing and processing that data. Cloud ingress and egress fees, expanding storage requirements, AI inference costs and growing data volumes are exposing the limitations of data architectures designed for an earlier generation of enterprise applications. 

This shift is creating a new infrastructure category. Enterprises no longer need another data pipeline; they need an agentic data control plane that can intelligently reduce, enrich, govern and activate data for both enterprise applications and AI systems. DataBahn is positioned to define this category through its technical architecture, execution and neutrality across the enterprise technology ecosystem. 

The Series B funding will accelerate investments in R&D and product innovation, expanding DataBahn’s agentic data control plane to serve organizations of every size, from large global enterprises to mid-market businesses. 

As the enterprise data market works through its present evolution, DataBahn can be thought of as the intelligent connective tissue for enterprise data. Traditional data pipelines were designed to move data from a source to a destination in a single direction, an architecture that once worked well. But now organizations need to control cloud egress costs, retain ownership of their data, and provide AI systems with secure access to rich enterprise context without replicating everything into another platform. 

Unlike traditional data pipelines that simply move data from one system to another, DataBahn intelligently governs, orchestrates and activates enterprise data across sources, destinations and AI models. It continuously reduces, enriches and routes only the data required for real-time operations while retrieving additional enterprise context on demand. The result is richer context for AI, faster decisions, and dramatically lower storage, compute, AI token, and cloud data movement costs. 

“Traditional data pipelines were built to move data. AI is changing every enterprise application, and AI is only as good as the enterprise data it can understand,” said Nanda Santhana, CEO and co-founder of DataBahn. “The next generation of enterprise infrastructure won’t be built around moving more data — it will be built around intelligently orchestrating the right data at the right time. We believe every enterprise will need an agentic data control plane that continuously reduces, enriches, governs and activates enterprise data for both applications and AI. Organizations that build this foundation will accelerate AI adoption while dramatically reducing the cost of moving, storing and processing data.” 

Read Santhana’s blog post on the funding round and why The Pipeline Was Never the Point.

DataBahn achieved early product-market fit by building an enterprise-grade platform designed for the scale, complexity and security requirements of some of the world’s largest organizations. That foundation enabled the company to scale primarily through channel and strategic partners. Today, DataBahn powers enterprise data operations for some of the world’s largest organizations, including Fortune 100 companies across healthcare, financial services, manufacturing and transportation. The results include more than 400% year-over-year revenue growth, 180% net revenue retention, zero customer churn, and a 97% proof-of-concept win rate. 

“The next generation of enterprise infrastructure won’t be defined by where data is stored, but by how intelligently it can be orchestrated for AI,” said Max Wolff, Managing Director at Insight Partners. “DataBahn is building that layer, and enterprise leaders across industries describe DataBahn as foundational to their future security architecture. We look forward to supporting the team through this next stage of growth.” 

In its Trends Report: The Future Of Data Modeling, April 2026, Forrester Research observed that “Organizations face growing pressure to scale AI and analytics, yet fragmented data models and inconsistent definitions remain major obstacles.” And, in Best Practices To Optimize AI Data Fabrics, February 2026, Forrester reported that, “A modern AI-enabled data fabric provides the intelligent foundation for delivering trusted, accessible, and governed data to support advanced analytics and informed decision-making.”

DataBahn Customer Voices
“DataBahn’s agentic data control plane helped us modernize and streamline our processes, which was key in supporting our fleet of AI agents. Their platform ingests multiple data formats from diverse sources while incorporating our regulatory requirements, audit controls and validation processes into a single, cohesive solution,” said Parrish Gunnels, CISO, MVB Bank. “The results have been significant. We have realized savings while improving consistency and reliability. More importantly, we have been able to redirect valuable team resources toward higher-value governance, risk management and oversight activities.” 

“Our telemetry was fragmented across multiple platforms and teams. Onboarding a new log source took custom integrations and significant engineering effort, and we had limited insight into whether critical systems were actually sending logs as expected,” said Ricardo Henry, Lead, Security Architecture & Engineering, Information & Corporate Security at the Canada Pension Plan Investment Board (CPPIB). “DataBahn gave us a standardized, repeatable way to onboard security data. New sources come online more efficiently, we can identify coverage gaps quickly, and as a result the platform has become an important part of our operational ecosystem. As our logging requirements have grown, it has flexed to support new data sources and use cases without extensive rework.”

DataBahn will preview new capabilities in its agentic data control plane at Black Hat USA 2026, booth # 5923. 

About DataBahn
DataBahn is the Agentic Data Control Plane for the enterprise. Its platform ingests, normalizes, enriches, governs, and routes telemetry from 600+ sources with complete data and AI neutrality: any source, any destination, any model, no vendor lock-in, at Fortune 100 scale. DataBahn is headquartered in Dallas and serves Fortune 500 enterprises. Learn more at databahn.ai. 

About Insight Partners
Insight Partners is a global software investor partnering with high-growth technology, software, and Internet startup and ScaleUp companies that are driving transformative change in their industries. As of December 31, 2025, the firm has over $90B in regulatory assets under management. Insight Partners has invested in more than 900 companies worldwide and has seen over 55 portfolio companies achieve an IPO. Headquartered in New York City, Insight has a global presence with leadership in London, Tel Aviv, and the Bay Area. Insight’s mission is to find, fund, and work successfully with visionary executives, providing them with tailored, hands-on software expertise along their growth journey, from their first investment to IPO. For more information on Insight and all its investments, visit insightpartners.com or follow us on X @insightpartners.

Media Contact:
Cristin Connelly
Cathey Communications for DataBahn
[email protected]

SOURCE DataBahn

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