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SiliconANGLE AI · 2026/7/30 14:00:00

DataBahn raises $40M as AI agents queue up for enterprise telemetry
AI 中文解读
**1. 核心亮点:**
企业数据管道初创公司DataBahn融了4000万美元,打造“AI数据控制中心”——让数据在传输途中就被智能精简和定向投喂,不再一股脑全存下来。
**2. 通俗解读:**
以前,企业收集的各种系统日志、传感器数据,传统做法是先一股脑存进仓库,再用工具慢慢分析。但现在,AI助手和智能代理(比如客服机器人、内部审计AI)也跑来要数据了,它们不需要原始日志,而是需要“有上下文的有用信息”。DataBahn就像一个智能数据管家,它架在数据产生源头和AI工具之间,实时筛选:哪些数据该留、哪些该精简,还能按需补充企业背景,比如员工权限、业务规则。最核心的是,数据不用提前复制到另一个平台,省去大量存储和云传输费用。
**3. 实际影响:**
对普通人来说,这意味着你使用的银行App、医疗预约系统或企业内网AI助手会变得更“懂你”且响应更快,因为后台数据已经过精准调教。企业也能大幅降低云服务账单(省下的钱可能体现在更低的产品价格上),同时合规性更强——比如金融机构能更精细地控制哪些数据可以被AI读取,保护用户隐私。简单说,就是AI为企业工作时,既快又省钱,还更安全。
UPDATED 10:00 EDT / JULY 30 2026
BIG DATA
DataBahn raises $40M as AI agents queue up for enterprise telemetry
by
Duncan Riley
Enterprise data pipeline startup DataBahn Inc. today revealed that it has raised $40 million in new funding to accelerate development of what it calls an agentic data control plane.
Founded in 2024, DataBahn sells software that sits between the systems generating enterprise telemetry and the tools that consume it. The platform ingests, normalizes and routes data from more than 600 sources, stripping out what the destination does not need along the way. The company also pitches neutrality, with no lock-in to a given destination or artificial intelligence model.
Security platforms, data warehouses and analytics tools were the traditional consumers of that telemetry. AI agents and copilots have joined the queue, and they want context rather than raw logs. Cost is the other pressure point, since cloud ingress and egress fees, storage and AI inference bills all scale with volume.
DataBahn’s pitch is that the decision about what data moves should be made in transit. Its software reduces and enriches telemetry as it flows, forwards only what real-time operations require and retrieves additional enterprise context on demand. Nothing has to be copied wholesale into another platform first.
“Traditional data pipelines were built to move data. AI is changing every enterprise application, and AI is only as good as the enterprise data it can understand,” said Nanda Santhana, chief executive and co-founder of DataBahn. “We believe every enterprise will need an agentic data control plane that continuously reduces, enriches, governs and activates enterprise data for both applications and AI.”
The company sells largely through channel and strategic partners. It says that model has produced revenue growth of more than 400% year-over-year, net revenue retention of 180% and no customer churn to date, along with a 97% win rate on proofs of concept. Customers include Fortune 100 companies in healthcare, financial services, manufacturing and transportation.
Parrish Gunnels, chief information security officer at MVB Bank Inc., said DataBahn pulled the bank’s regulatory requirements, audit controls and validation processes into “a single, cohesive solution,” cutting costs and freeing staff to work on governance and oversight. Ricardo Henry, who leads security architecture and engineering at the Canada Pension Plan Investment Board, said onboarding a new log source used to require custom integrations and considerable engineering time, with little visibility into whether critical systems were sending logs at all. He said DataBahn gave the fund a “standardized, repeatable way to onboard security data” and made coverage gaps easier to identify.
The new money goes into research and development, with the company aiming to push the platform down from large global enterprises into the mid-market. DataBahn will preview additions to the platform at Black Hat USA 2026.
Insight Partners LP led the Series B round, with participation from existing investors Forgepoint Capital, GTM Capital and S3 Ventures. Max Wolff, a managing director at Insight Partners, said enterprise leaders across industries describe DataBahn as “foundational to their future security architecture.”
DataBahn closed a $17 million Series A led by Forgepoint Capital in June 2025. Total funding now stands at $59 million.
Photo: DataBahn
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