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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."

The Latest

Artificial intelligence (AI) is core to observability practices, with some 41% of respondents reporting AI adoption as a core driver of observability, according to the State of Observability for Financial Services and Insurance report from New Relic ...

Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...

Cloud adoption has accelerated, but backup strategies haven't always kept pace. Many organizations continue to rely on backup strategies that were either lifted directly from on-prem environments or use cloud-native tools in limited, DR-focused ways ... Eon uncovered a handful of critical gaps regarding how organizations approach cloud backup. To capture these prevailing winds, we gathered insights from 150+ IT and cloud leaders at the recent Google Cloud Next conference, which we've compiled into the 2025 State of Cloud Data Backup ...

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

Back in March of this year ... MongoDB's stock price took a serious tumble ... In my opinion, it reflects a deeper structural issue in enterprise software economics altogether — vendor lock-in ...

In MEAN TIME TO INSIGHT Episode 15, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses Do-It-Yourself Network Automation ... 

Zero-day vulnerabilities — security flaws that are exploited before developers even know they exist — pose one of the greatest risks to modern organizations. Recently, such vulnerabilities have been discovered in well-known VPN systems like Ivanti and Fortinet, highlighting just how outdated these legacy technologies have become in defending against fast-evolving cyber threats ... To protect digital assets and remote workers in today's environment, companies need more than patchwork solutions. They need architecture that is secure by design ...

Traditional observability requires users to leap across different platforms or tools for metrics, logs, or traces and related issues manually, which is very time-consuming, so as to reasonably ascertain the root cause. Observability 2.0 fixes this by unifying all telemetry data, logs, metrics, and traces into a single, context-rich pipeline that flows into one smart platform. But this is far from just having a bunch of additional data; this data is actionable, predictive, and tied to revenue realization ...

64% of enterprise networking teams use internally developed software or scripts for network automation, but 61% of those teams spend six or more hours per week debugging and maintaining them, according to From Scripts to Platforms: Why Homegrown Tools Dominate Network Automation and How Vendors Can Help, my latest EMA report ...