The enterprise AI landscape is rapidly evolving, with companies eager to leverage AI agents for various tasks. However, a critical bottleneck has emerged: AI agents often lack the nuanced understanding of internal data, leading to unreliable outputs and stalled deployments. Euno, an AI-native context platform, addresses this by providing a governed organizational context that enables AI agents to interpret enterprise data accurately and reliably.

Euno recently announced a $23 million Series A funding round, bringing its total capital raised to $29 million. The round was led by N47, with participation from existing investor 10D and a group of prominent technology founders, including Yinon Kostika of Wiz and Mark Nelson, former CEO of Tableau. This investment underscores investor confidence in Euno's approach to solving the 'context problem' for enterprise AI.

The platform functions as a metadata intelligence layer, continuously learning how organizations build, use, and govern their data. By reconstructing institutional knowledge from evolving metadata patterns, Euno delivers trusted data context to external AI agents at query time, tailored to user personas and tasks. This capability aims to accelerate AI initiatives, moving them from pilot to production within weeks, a significant improvement over traditional, time-consuming data preparation methods.

Unlike generic data integration tools, Euno focuses specifically on providing semantic understanding and governance automation for AI agents. This specialized approach allows enterprises to deploy autonomous agents with confidence, ensuring data accuracy and compliance. The funding will primarily be allocated to sales, marketing, and further AI research, as Euno plans to double its nearly 30-person workforce by year-end.