Modus Raises $10M Seed Led by Insight Partners to Build the Context Warehouse for Enterprise AI

Discover AnythingSignupWrite New StoryModus Raises $10M Seed Led by Insight Partners to Build the Context Warehouse for Enterprise AIbyruth_hassonbyruth_hasson|@ruth-hassonA tech newsdesk dispatching breaking software, fintech, AI and innovation updates across global publisher network.SubscribeJuly 29th, 2026TLDR Your browser does not support the audio element.Speed1xVoiceDr. One Ms. Hacker byruth_hasson@ruth-hassonbyruth_hasson|@ruth-hassonA tech newsdesk dispatching breaking software, fintech, AI and innovation updates across global publisher network.SubscribeStory's Credibilitybyruth_hasson|@ruth-hassonA tech newsdesk dispatching breaking software, fintech, AI and innovation updates across global publisher network.SubscribeStory's Credibility The enterprise AI market has spent much of its early development focused on making models more capable and connecting them to more information. But as companies begin deploying AI agents in production, a different challenge is becoming apparent: knowing what information those agents should actually use.Modus believes the next layer of enterprise AI infrastructure will need to address that problem. According to a report by Axios, the company has emerged from stealth with a $10 million seed round led by Insight Partners, with participation from Soma Capital, Bullet Ventures, and technology founders and operators including Eyal Kishon, Nadav Avrami of Wix and Dazl, the co-founders of Cyera, and the founders of Epsagon. The company's answer is the Context Warehouse, an infrastructure layer designed to continuously learn how a business operates and provide AI agents with only the context relevant to a particular interaction. More Data Does Not Necessarily Mean Better AI Enterprise AI systems can already access a wide range of corporate information. Data warehouses, BI tools, documents, tickets, code repositories, pipelines, and collaboration platforms can all provide material for AI systems to retrieve. The difficulty, according to Modus, is that access does not automatically create understanding. An AI agent may be able to find a dashboard without knowing whether employees actually rely on it, or encounter multiple definitions of a metric without knowing which one the business considers authoritative. That creates what Modus calls the "Context Gap"—the distance between what AI can access and how the business actually works. Agents can over-fetch information, repeatedly query enterprise systems, and consume unnecessary tokens, potentially making AI deployments more expensive, slower, and less reliable. "Companies are no longer just trying to get their teams to use AI. They are asking how to scale it across the organization without accuracy dropping, governance breaking, or costs spiraling," said Daniel Shimoni, CEO and co-founder of Modus. "Whether people call it a company brain, a context layer, or context engineering, they are all trying to solve the same problem. We believe every enterprise needs a continuously maintained understanding of how the business operates before it can build any of those things. That is what the Context Warehouse provides." A System That Learns From Enterprise Behavior Modus is positioning the Context Warehouse as a new foundational layer for enterprise AI. The company's broader thesis is that, just as data warehouses became systems of record for enterprise data, AI will require a system of understanding that can keep pace with how organizations operate. The platform is designed to learn from metadata and usage patterns across a company's existing technology environment. That includes data warehouses, BI tools, pipelines, code repositories, documentation, and collaboration systems. It also looks at the ways employees interact with those systems. Recurring analyst queries, frequently used dashboards, pipelines, and decision threads can provide signals about how the business actually operates, including knowledge that may not be formally documented. Modus says th