Euno Raises $23M For Context Layer Behind Enterprise AI Agents
Euno raised $23 million in Series A funding led by N47 to expand an AI-native context platform that helps enterprise agents use business data with governance controls.
Euno has raised $23 million to build what it calls an AI-native context brain for autonomous agents, SiliconANGLE reported, giving the Israeli startup fresh capital for a data layer meant to make enterprise agents more reliable.
The Series A round was led by N47 and included 10D, which previously led Euno's seed round.
Angel investors in the financing included Wiz co-founder Yinon Kostika, Cyera co-founder Yotam Segev, Eon co-founder Ofir Ehrlich and Tavily founder Rotem Weiss.
The company, legally named Delphi.io Inc, has now raised $29 million in total.
Euno's product targets a problem that has kept many agentic AI projects in prototype form: the gap between business data that humans can interpret and data that machines can act on safely.
The platform studies how an organization creates, uses and governs its information, then turns that institutional knowledge into a context layer that agents can query while completing specific tasks.
Chief Executive Sarah Levy framed trust as the main adoption barrier.
Enterprises worry that agents may hallucinate, misread business context or act outside the rules that govern sensitive data.
In her description, the challenge is not only access to data but also the meaning attached to it: how one data set connects to another, when a record can be trusted and which operational rule should apply.
Many companies have tried to solve that by writing large stores of documentation for their AI systems.
Euno is trying to replace that manual process with a live model of institutional context.
Its system analyzes changing metadata graphs, infers the knowledge that normally sits inside teams and workflows, and folds governance rules into the context that each agent can use.
The mechanism matters because Euno is not pitching a replacement for employees or a new frontier model.
Its product sits between existing enterprise systems and agent workflows, watching how metadata and governance patterns change as teams keep working.
That lets the context layer update as business rules, permissions and data relationships change instead of forcing staff to maintain thousands of static instruction pages.
Levy put the time saving in concrete terms, saying Euno can cut preparation of a context layer for agentic deployments from as long as a year to a few weeks.
She also argued that an enterprise's accumulated record of how work gets done can become an AI moat because competitors may use similar frontier models but cannot easily copy internal operating experience.
The startup points to Zayo Group Holdings and AlphaSense as large-enterprise customers that have used the context brain to accelerate agent deployments.
The new funding is intended to build on that traction while expanding the company beyond its current team of about 30 employees.
Hiring is part of the transaction story.
Euno wants to double headcount by the end of next year, adding staff across research, sales and marketing.
N47 partner Moshe Zilberstein linked the investment case to demand for agents that can work on current, trusted business data without introducing mistakes, making the funding a bet on contextual infrastructure rather than another general-purpose model.
