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The world is creating extra information than enterprises can realistically handle. In 2024, world information creation is predicted to hit 149 zettabytes. By 2028, that quantity is projected to almost triple, reaching greater than 394 zettabytes. For giant organizations, the problem is now not nearly storage; it’s about tips on how to deal with that scale intelligently, with out overwhelming infrastructure or slowing down selections.
DataBahn.ai, a Texas-based startup centered on AI-driven information pipeline automation, is getting into that hole. The corporate has raised $17 million in Collection A funding to develop its platform, which helps enterprises automate and streamline how information strikes throughout safety, observability, and AI methods.
The most recent funding spherical was led by Forgepoint Capital, with participation from S3 Ventures and returning investor GTM Capital, bringing its complete funding to $19 million.
Forgepoint Capital managing director Ernie Bio, who led the spherical and has joined DataBahn’s board, mentioned the corporate is tackling actual and rising infrastructure challenges. As enterprises face rising volumes of information from cloud, AI, and related methods, many are nonetheless counting on legacy SIEM instruments which are too pricey and too inflexible to scale.
Based on DataBahn, its AI-driven platform helps streamline information flows, lower SIEM prices by over 50%, and automate greater than 80% of information engineering work. Bio cited sturdy early adoption, speedy ROI, and a extremely responsive staff as indicators that the corporate is well-positioned to develop and assist enterprises make sense of their information with out overhauling their complete stack.
The startup shared that new funding shall be used to develop the platform with extra superior autonomous AI capabilities and to assist the corporate’s world development plans. A key focus is constructing out agent-based instruments that may be taught from enterprise information in actual time, serving to groups automate complicated engineering duties with out guide effort.
DataBahn was based in July 2024 by a staff with backgrounds in cybersecurity, enterprise information, and operational threat. CEO Nanda Santhana had beforehand helped launch Securonix and served as a tech fellow at Oracle. President Nithya Nareshkumar introduced management expertise from JPMorgan and DTCC.
The startup’s early focus was on considered one of enterprise safety’s extra persistent challenges: managing the quantity and complexity of information flowing from methods like IoT networks, OT environments, and SOC infrastructure. Most instruments weren’t constructed for that form of operational noise, and the corporate noticed a possibility to construct pipelines that had been extra purpose-built for the fact of safety environments.
Since then, the corporate has expanded its scope. What started as a security-specific resolution has grown right into a broader management layer that brings order to information throughout infrastructure, purposes, and AI methods.
A key a part of the platform, based on the corporate, is its use of Phantom brokers—light-weight AI modules designed to gather, clear, and enrich information in actual time. DataBahn says these brokers keep away from the overhead typical of conventional software program, permitting groups to handle rising information volumes with out sacrificing efficiency or including pointless complexity.
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The corporate additionally highlights its federated search capabilities as a key differentiator. Slightly than relying on structured queries, the system surfaces insights based mostly on a consumer’s position and duties. This implies observability groups can anticipate points earlier than they escalate, safety groups can determine threats extra shortly, and enterprise customers achieve a clearer image of how purposes are performing—all with out having to sift by way of uncooked information or depend on customized queries.
“Right now’s enterprises don’t simply want information pipelines; they want clever materials that adapt, govern, and optimize information at scale,” mentioned Nanda Santhana, co-founder and CEO of DataBahn.ai. “We’re constructing the muse for a brand new period of observability, one the place information isn’t just moved, however understood, enriched, and made AI-ready in actual time.”
DataBahn factors to a Forrester weblog publish that displays its personal considering on how enterprise information infrastructure wants to vary. The publish explains that purpose-built pipeline instruments are usually not nearly transferring information from one place to a different. Additionally they assist cut back the trouble required to arrange that information by routing, enriching, redacting, and reworking it alongside the best way.
This turns into particularly helpful in safety environments, the place groups are sometimes working with fragmented methods and inconsistent indicators. For DataBahn, the precedence is just not merely making information accessible, however making it usable in context.
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That emphasis on usability is already resonating with enterprise groups. A few of DataBahn’s early clients are seeing measurable enhancements in how they handle, perceive, and act on their information. A type of organizations is CSL Behring.
“This product has modified what information means to us. Our journey with DataBahn has reworked information from a value heart right into a strategic asset. I’d suggest this to each CISO and IT chief seeking to take management of their information,” mentioned Greg Stewart, senior director of cybersecurity and menace intelligence at CSL Behring.
With contemporary funding and rising curiosity from clients, DataBahn is targeted on serving to groups get extra worth from the info they already accumulate. In an area crowded with instruments that floor extra information, its pitch is straightforward: make the pipelines smarter, and every little thing downstream will get simpler.
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