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DataBahn.ai Raises $17M Series A Funding

DataBahn.ai raised $17 million in Series A funding. 

The round was led by Forgepoint Capital, with participation from S3 Ventures and returning investor GTM Capital, bringing the company's total capital raised to $19 million.

The funding will accelerate the development of the DataBahn platform roadmap for agentic AI — autonomous agents that learn from enterprise data flows to automate data engineering tasks—and support global expansion as the company establishes itself as the trusted foundation for enterprises seeking clarity, control and composability in their data pipelines.      

DataBahn.ai is setting a new benchmark for how modern enterprises manage and operationalize telemetry across security, observability, IOT/OT and AI ecosystems. The DataBahn platform delivers a dynamic, AI-native data fabric that allows organizations to seamlessly integrate, govern and optimize data pipelines from any source to any destination — with one-click simplicity and enterprise-grade control.

DataBahn's new Phantom agents collect telemetry without deploying traditional agents, avoiding footprint bloat and preserving compute resources. Built on a revolutionary AI-driven architecture, DataBahn parses, enriches and suppresses noise at scale, all while also being mindful of egress costs. The platform's new federated search capabilities deliver persona-based insights; it's beyond just using SQL queries. For security teams, this means faster threat detection and streamlined compliance. For observability teams, better predictive analytics for IT outage prevention. For business teams, deeper application transaction visibility. For the enterprise as a whole, DataBahn unlocks the full value of data — without compromise.

"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."

"Enterprises aren't just overwhelmed by data volume; they're being outpaced by its complexity," said Santhana. "Our mission is to transform telemetry from a liability into a strategic asset by making data pipelines smarter, leaner and AI-ready from the start."

As part of the Series A round, Ernie Bio, managing director at Forgepoint Capital, has joined the DataBahn.ai board of directors. "DataBahn is tackling one of the most urgent infrastructure challenges: how to manage and extract value from fragmented, fast-growing data streams," said Bio. "What's truly rare is the customer enthusiasm. We heard consistent praise for the platform's rapid ROI, forward-looking innovation and the team's responsiveness—qualities that separate great companies from the rest."

Originally designed to address the unique challenges of cybersecurity, IoT and OT telemetry, the DataBahn platform has rapidly evolved into a unified control plane for enterprise data. Its expansion into application, infrastructure and observability workloads reflects a growing demand for intelligent, end-to-end visibility across the modern data lifecycle.

"We didn't set out to build just another pipeline. We built DataBahn to make data work for security and IT teams—not the other way around" said Nithya Nareshkumar, co-founder and president of DataBahn.ai. "By combining deep domain knowledge with plug-and-play AI, we're helping teams break through complexity and unlock insight from day one—no rewiring, no retraining."

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DataBahn.ai Raises $17M Series A Funding

DataBahn.ai raised $17 million in Series A funding. 

The round was led by Forgepoint Capital, with participation from S3 Ventures and returning investor GTM Capital, bringing the company's total capital raised to $19 million.

The funding will accelerate the development of the DataBahn platform roadmap for agentic AI — autonomous agents that learn from enterprise data flows to automate data engineering tasks—and support global expansion as the company establishes itself as the trusted foundation for enterprises seeking clarity, control and composability in their data pipelines.      

DataBahn.ai is setting a new benchmark for how modern enterprises manage and operationalize telemetry across security, observability, IOT/OT and AI ecosystems. The DataBahn platform delivers a dynamic, AI-native data fabric that allows organizations to seamlessly integrate, govern and optimize data pipelines from any source to any destination — with one-click simplicity and enterprise-grade control.

DataBahn's new Phantom agents collect telemetry without deploying traditional agents, avoiding footprint bloat and preserving compute resources. Built on a revolutionary AI-driven architecture, DataBahn parses, enriches and suppresses noise at scale, all while also being mindful of egress costs. The platform's new federated search capabilities deliver persona-based insights; it's beyond just using SQL queries. For security teams, this means faster threat detection and streamlined compliance. For observability teams, better predictive analytics for IT outage prevention. For business teams, deeper application transaction visibility. For the enterprise as a whole, DataBahn unlocks the full value of data — without compromise.

"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."

"Enterprises aren't just overwhelmed by data volume; they're being outpaced by its complexity," said Santhana. "Our mission is to transform telemetry from a liability into a strategic asset by making data pipelines smarter, leaner and AI-ready from the start."

As part of the Series A round, Ernie Bio, managing director at Forgepoint Capital, has joined the DataBahn.ai board of directors. "DataBahn is tackling one of the most urgent infrastructure challenges: how to manage and extract value from fragmented, fast-growing data streams," said Bio. "What's truly rare is the customer enthusiasm. We heard consistent praise for the platform's rapid ROI, forward-looking innovation and the team's responsiveness—qualities that separate great companies from the rest."

Originally designed to address the unique challenges of cybersecurity, IoT and OT telemetry, the DataBahn platform has rapidly evolved into a unified control plane for enterprise data. Its expansion into application, infrastructure and observability workloads reflects a growing demand for intelligent, end-to-end visibility across the modern data lifecycle.

"We didn't set out to build just another pipeline. We built DataBahn to make data work for security and IT teams—not the other way around" said Nithya Nareshkumar, co-founder and president of DataBahn.ai. "By combining deep domain knowledge with plug-and-play AI, we're helping teams break through complexity and unlock insight from day one—no rewiring, no retraining."

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Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...

In today's fast-paced AI landscape, CIOs, IT leaders, and engineers are constantly challenged to manage increasingly complex and interconnected systems. The sheer scale and velocity of data generated by modern infrastructure can be overwhelming, making it difficult to maintain uptime, prevent outages, and create a seamless customer experience. This complexity is magnified by the industry's shift towards agentic AI ...

In MEAN TIME TO INSIGHT Episode 19, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA explains the cause of the AWS outage in October ... 

The explosion of generative AI and machine learning capabilities has fundamentally changed the conversation around cloud migration. It's no longer just about modernization or cost savings — it's about being able to compete in a market where AI is rapidly becoming table stakes. Companies that can't quickly spin up AI workloads, feed models with data at scale, or experiment with new capabilities are falling behind faster than ever before. But here's what I'm seeing: many organizations want to capitalize on AI, but they're stuck ...

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Poor DEX directly costs global businesses an average of 470,000 hours per year, equivalent to around 226 full-time employees, according to a new report from Nexthink, Cracking the DEX Equation: The Annual Workplace Productivity Report. This indicates that digital friction is a vital and underreported element of the global productivity crisis ...