With $17M in Funding, DataBahn Pushes AI Agents to Reinvent the Enterprise Data Pipeline

The world is creating more data than enterprises can realistically manage. In 2024, global data creation is expected to hit 149 zettabytes. By 2028, that number is projected to nearly triple, reaching more than 394 zettabytes. For large organizations, the challenge is no longer just about storage; it’s about how to handle that scale intelligently, without overwhelming infrastructure or slowing down decisions.

DataBahn.ai, a Texas-based startup focused on AI-driven data pipeline automation, is stepping into that gap. The company has raised $17 million in Series A funding to grow its platform, which helps enterprises automate and streamline how data moves across security, observability, and AI systems.

The latest funding round was led by Forgepoint Capital, with participation from S3 Ventures and returning investor GTM Capital, bringing its total funding to $19 million.

Forgepoint Capital managing director Ernie Bio, who led the round and has joined DataBahn’s board, said the company is tackling real and growing infrastructure challenges. As enterprises face rising volumes of data from cloud, AI, and connected systems, many are still relying on legacy SIEM tools that are too costly and too rigid to scale.

According to DataBahn, its AI-driven platform helps streamline data flows, cut SIEM costs by over 50%, and automate more than 80% of data engineering work. Bio cited strong early adoption, rapid ROI, and a highly responsive team as signs that the company is well-positioned to grow and help enterprises make sense of their data without overhauling their entire stack.

The startup shared that new funding will be used to expand the platform with more advanced autonomous AI capabilities and to support the company’s global growth plans. A key focus is building out agent-based tools that can learn from enterprise data in real time, helping teams automate complex engineering tasks without manual effort.

DataBahn was founded in July 2024 by a team with backgrounds in cybersecurity, enterprise data, and operational risk. CEO Nanda Santhana had previously helped launch Securonix and served as a tech fellow at Oracle. President Nithya Nareshkumar brought leadership experience from JPMorgan and DTCC.

The startup’s early focus was on one of enterprise security’s more persistent challenges: managing the volume and complexity of data flowing from systems like IoT networks, OT environments, and SOC infrastructure. Most tools weren’t built for that kind of operational noise, and the company saw an opportunity to build pipelines that were more purpose-built for the reality of security environments.

Since then, the company has expanded its scope. What began as a security-specific solution has grown into a broader control layer that brings order to data across infrastructure, applications, and AI systems.

A key part of the platform, according to the company, is its use of Phantom agents—lightweight AI modules designed to collect, clean, and enrich data in real time. DataBahn says these agents avoid the overhead typical of traditional software, allowing teams to manage growing data volumes without sacrificing performance or adding unnecessary complexity.

(LuckyStep/Shutterstock)

The company also highlights its federated search capabilities as a key differentiator. Rather than depending on structured queries, the system surfaces insights based on a user’s role and responsibilities. This means observability teams can anticipate issues before they escalate, security teams can identify threats more quickly, and business users gain a clearer picture of how applications are performing—all without having to sift through raw data or rely on custom queries.

“Today’s enterprises don’t just need data pipelines; they need intelligent fabrics that adapt, govern, and optimize data at scale,” said Nanda Santhana, co-founder and CEO of DataBahn.ai. “We’re building the foundation for a new era of observability, one where data is not just moved, but understood, enriched, and made AI-ready in real time.”

DataBahn points to a Forrester blog post that reflects its own thinking on how enterprise data infrastructure needs to change. The post explains that purpose-built pipeline tools are not just about moving data from one place to another. They also help reduce the effort required to prepare that data by routing, enriching, redacting, and transforming it along the way.

This becomes especially useful in security environments, where teams are often working with fragmented systems and inconsistent signals. For DataBahn, the priority is not simply making data available, but making it usable in context.

(Wanan Wanan/Shutterstock)

That emphasis on usability is already resonating with enterprise teams. Some of DataBahn’s early customers are seeing measurable improvements in how they manage, understand, and act on their data. One of those organizations is CSL Behring.

“This product has changed what data means to us. Our journey with DataBahn has transformed data from a cost center into a strategic asset. I’d recommend this to every CISO and IT leader looking to take control of their data,” said Greg Stewart, senior director of cybersecurity and threat intelligence at CSL Behring.

With fresh funding and growing interest from customers, DataBahn is focused on helping teams get more value from the data they already collect. In a space crowded with tools that surface more data, its pitch is simple: make the pipelines smarter, and everything downstream gets easier.

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