Euno, an enterprise AI context platform designed to help organizations give AI agents trusted business and data context, has raised $23 million in Series A funding led by N47. The financing brings the company’s total funding to $29 million. Existing investor 10D also participated, along with technology founders and executives including Wiz co-founder Yinon Kostika, Cyera co-founder and CEO Yotam Segev, Eon co-founder and CEO Ofir Ehrlich, Tavily founder Rotem Weiss, and former Tableau CEO and President Mark Nelson.
Euno is building what it describes as an AI-native “context brain” for enterprises. Its platform continuously learns how organizations create, use, and govern data so AI agents can better understand what information means, which data should be trusted, and how different pieces of information connect across the business.
That problem is becoming more important as companies move beyond AI assistants that answer questions toward autonomous agents capable of taking actions across multiple systems.
While AI models can access enterprise data, Euno argues that raw access does not provide the organizational knowledge needed to use that information reliably. An agent may need to understand definitions, ownership, lineage, policies and how employees actually use particular datasets before it can make a trustworthy decision.
Euno’s platform is designed to reconstruct that knowledge automatically rather than depend primarily on manually maintained catalogs and documentation.
The system analyzes how data flows through an organization and how it is used, then provides each AI agent with the specific context required for its task. As agents interact with that information, their activity creates additional feedback that Euno uses to continuously update the organization’s context layer.
The company believes this creates a compounding advantage for enterprises. While competing organizations may have access to many of the same frontier AI models, each company’s accumulated operational knowledge and understanding of how work gets done can become proprietary infrastructure for its AI systems.
Euno’s research has focused in part on determining how much institutional knowledge can be inferred from operational signals instead of requiring employees to document everything manually.
The company said important information about which data to use, what to trust and how data should be interpreted can often be inferred from patterns across continuously changing metadata graphs. Euno analyzes those patterns and then refines its understanding through feedback generated by agents.
According to Euno, this approach can reduce the time required to move enterprise AI projects into production from roughly a year of preparation to weeks.
Governance is built directly into the platform. Euno can control which context each agent receives based on its role and task while enforcing organizational access boundaries in real time.
That capability addresses one of the key obstacles enterprises face as they experiment with autonomous AI agents: organizations may be reluctant to connect agents to sensitive corporate systems when they cannot clearly determine what those agents will be able to access.
Euno is already working with Fortune 500 companies and other enterprises. Customers include market intelligence platform AlphaSense and telecommunications company Zayo Group.
Zayo has used Euno as an alternative to the traditional process of manually building and maintaining a data catalog. The company said the approach reduced the amount of time required to establish governance without first creating complex canonical data models.
Euno was founded in 2023 by Sarah Levy and Eyal Firstenberg, both graduates of Talpiot, the Israeli military’s technology program.
Levy previously served as CTO of Sight Diagnostics and led an IDF cybersecurity department. Firstenberg previously held a leadership role in Unit 8200 and later served as Vice President of Research and Development at LightCyber, which Palo Alto Networks acquired.
The company currently employs nearly 30 people across the U.S. and Israel, including a dedicated context research team. Euno expects to approximately double its workforce by the end of 2026, with the Series A primarily supporting sales, marketing and AI research.
Euno has also been recognized in Gartner’s 2026 Coolest Vendor Innovations in Data Management report for its continuously updated enterprise context graph and its ability to give AI systems semantic understanding of corporate data assets.
The larger opportunity for Euno is tied to the growing number of companies attempting to move agentic AI from experiments into production. As models become more capable and less expensive, Euno sees enterprise-specific context, rather than access to the models themselves, becoming an increasingly important differentiator.
KEY QUOTES:
“Models keep getting better and cheaper, but the long-term AI moat for enterprises will increasingly come from the accumulated record of how work gets done. Competitors may have access to the same frontier models, but they cannot easily replicate the proprietary context and experience an enterprise has accumulated through its own operations. The teams that own enterprise data have been the ones slowing AI down, and they were right to do so because nobody could tell them what an agent would be able to reach once it was connected. Security vendors sell them the fear. We hand them the ability to actually deploy and build the organizations of the future.”
Sarah Levy, Co-Founder and CEO of Euno
“Enterprises are thirsty for impact-making AI agents. For an AI agent to move the needle, it must act on current and trusted business data – and that demands precise, scalable contextual infrastructure. Demand for this AI infrastructure is accelerating fast, and Euno is the only company building it AI-native instead of retrofitting a solution meant for people.”
Moshe Zilberstein, General Partner at N47
“After years of implementing data governance solutions at the top two telecom providers in the United States, encountering Euno was a turning point. With it, I realized we no longer needed to follow the traditional playbook and build a data catalog, but could leap ahead with an AI-driven approach. This shift saved significant time, without needing to build complex models or manually create canonical models.”
Will Mitchell, Director of Data and AI Governance at Zayo
