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The world is creating extra knowledge than enterprises can realistically handle. In 2024, international knowledge creation is anticipated 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 learn how to deal with that scale intelligently, with out overwhelming infrastructure or slowing down selections.
DataBahn.ai, a Texas-based startup targeted on AI-driven knowledge pipeline automation, is moving into that hole. The corporate has raised $17 million in Sequence A funding to develop its platform, which helps enterprises automate and streamline how knowledge strikes throughout safety, observability, and AI programs.
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, stated the corporate is tackling actual and rising infrastructure challenges. As enterprises face rising volumes of information from cloud, AI, and related programs, many are nonetheless counting on legacy SIEM instruments which might be too pricey and too inflexible to scale.
In line with DataBahn, its AI-driven platform helps streamline knowledge flows, lower SIEM prices by over 50%, and automate greater than 80% of information engineering work. Bio cited sturdy early adoption, fast ROI, and a extremely responsive crew as indicators that the corporate is well-positioned to develop and assist enterprises make sense of their knowledge with out overhauling their complete stack.
The startup shared that new funding might be used to broaden the platform with extra superior autonomous AI capabilities and to assist the corporate’s international progress plans. A key focus is constructing out agent-based instruments that may study from enterprise knowledge in actual time, serving to groups automate advanced engineering duties with out handbook effort.
DataBahn was based in July 2024 by a crew with backgrounds in cybersecurity, enterprise knowledge, 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 one in all enterprise safety’s extra persistent challenges: managing the amount and complexity of information flowing from programs like IoT networks, OT environments, and SOC infrastructure. Most instruments weren’t constructed for that sort of operational noise, and the corporate noticed a possibility to construct pipelines that had been extra purpose-built for the truth of safety environments.
Since then, the corporate has expanded its scope. What started as a security-specific answer has grown right into a broader management layer that brings order to knowledge throughout infrastructure, functions, and AI programs.
A key a part of the platform, in line with the corporate, is its use of Phantom brokers—light-weight AI modules designed to gather, clear, and enrich knowledge in actual time. DataBahn says these brokers keep away from the overhead typical of conventional software program, permitting groups to handle rising knowledge 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. Quite than relying on structured queries, the system surfaces insights based mostly on a person’s position and obligations. This implies observability groups can anticipate points earlier than they escalate, safety groups can establish threats extra shortly, and enterprise customers achieve a clearer image of how functions are performing—all with out having to sift by means of uncooked knowledge or depend on customized queries.
“As we speak’s enterprises don’t simply want knowledge pipelines; they want clever materials that adapt, govern, and optimize knowledge at scale,” stated Nanda Santhana, co-founder and CEO of DataBahn.ai. “We’re constructing the muse for a brand new period of observability, one the place knowledge 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 pondering on how enterprise knowledge infrastructure wants to vary. The publish explains that purpose-built pipeline instruments are usually not nearly shifting knowledge from one place to a different. Additionally they assist scale back the trouble required to arrange that knowledge by routing, enriching, redacting, and remodeling it alongside the way in which.
This turns into particularly helpful in safety environments, the place groups are sometimes working with fragmented programs and inconsistent indicators. For DataBahn, the precedence is just not merely making knowledge 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 knowledge. A kind of organizations is CSL Behring.
“This product has modified what knowledge means to us. Our journey with DataBahn has remodeled knowledge from a price middle right into a strategic asset. I’d suggest this to each CISO and IT chief trying to take management of their knowledge,” stated Greg Stewart, senior director of cybersecurity and menace intelligence at CSL Behring.
With recent funding and rising curiosity from clients, DataBahn is concentrated on serving to groups get extra worth from the information they already acquire. In an area crowded with instruments that floor extra knowledge, its pitch is straightforward: make the pipelines smarter, and every part downstream will get simpler.
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