Euno raises $23M to build the AI-native context brain for autonomous agents
SiliconANGLE Mike Wheatley
Euno raised $23M to build an AI “context brain” for agents. It wants to fix the trust problem that keeps enterprise AI stuck in prototype mode.
Based on reporting by SiliconANGLE, Mike Wheatley — read the original for the full story.
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Euno just pulled in $23 million to do a job that sounds abstract until you’ve watched an AI agent make something up in front of a business user. The Israeli startup says it is building an AI-native “context brain” for autonomous agents, and the bet is simple: enterprises won’t trust agents until they can act on current, trusted data.
The Series A was led by N47, with 10D joining alongside angels including Wiz co-founder Yinon Kostika, Cyera co-founder Yotam Segev, Eon co-founder Ofir Ehrlich and Tavily founder Rotem Weiss. With this round, Euno says total funding has reached $29 million.
The company, which is officially Delphi.io Inc., is aiming at a problem that sounds boring and turns out to be central. Business data is usually documented for humans, not machines. That makes it readable, but awkward for agents that need to understand what the data means, how it connects, and when it can be trusted. Sarah Levy, Euno’s co-founder and CEO, says that trust gap is one of the biggest reasons enterprise agent projects are still trapped in prototype land.
Euno’s answer is to infer context from operational signals instead of asking people to write endless documentation. It analyzes patterns across evolving metadata graphs, pulls out the institutional knowledge that matters most, and then folds in governance rules so each agent only gets the context it needs for the task at hand. Levy says that can cut preparation time for the context layer from up to a year to just a few weeks.
That pitch is already landing with some big companies. Euno says Zayo Group Holdings Inc. and AlphaSense Inc. have used its context brain to speed up agentic deployments. The company has about 30 employees now and plans to double that by the end of next year, adding to its research, sales and marketing teams. N47 partner Moshe Zilberstein’s view is that this kind of infrastructure has to be built natively for AI, not patched together from tools meant for people.
My take — AI-written commentary, not fact-checked reporting
This is the part of enterprise AI that actually matters: not bigger models, but better memory and tighter rules. Most agent hype skips straight past the ugly plumbing, then acts surprised when the robot wanders off the job. Euno is betting the moat is the company’s own operational history, and that sounds a lot more believable than another parade of demo magic.
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