Axios reports Insight Partners has led a $10 million seed round into Modus, a Tel Aviv startup emerging from stealth with an ambitious thesis: enterprise AI needs its own equivalent of the data warehouse, and Modus intends to own that category.
Soma Capital and Bullet Ventures joined the round. So did a notable list of technology founders and operators, including Eyal Kishon, Nadav Avrami of Wix and Dazl, the co-founders of Cyera, and the founders of Epsagon. For a seed-stage company, that is a cap table built for signaling as much as capital, and the signal is that experienced infrastructure builders see something worth backing.
The Investment Thesis
The bet rests on a pattern investors have seen before. Every major shift in enterprise software has produced a new foundational layer, and the companies that defined those layers captured enormous value. Data warehouses became the system of record for enterprise data. Modus argues that AI now requires a system of understanding, and it calls its version the Context Warehouse.
“Every major wave of enterprise software has required a new foundation,” said Ganesh Bell, Managing Director at Insight Partners. “Data warehouses became foundational infrastructure for enterprise data. As AI becomes production infrastructure, organizations need a system of understanding that every agent and application can build on. We believe Modus is defining that category with the Context Warehouse.”
The market timing argument is straightforward. Enterprises are racing to move AI from pilots into production, and many are discovering an expensive truth along the way. Connecting models to more systems often makes them slower, more costly, and less reliable. Agents over-fetch information, re-query enterprise systems, and consume far more tokens than they need because nothing tells them which context actually matters. Pilots stall. Costs spiral. Trust erodes.
Modus frames this as the Context Gap, the distance between what AI can access and how the business actually works. The problem, in the company’s view, is not too little context. It is too much of the wrong context.
What the Money Is Building
The Context Warehouse is infrastructure that continuously learns how a business operates and provides every AI interaction with only the relevant context it needs. It draws on structured data, unstructured data, and the tribal knowledge in between: the queries analysts keep returning to, the dashboards teams actually rely on, the pipelines, docs, and decision threads that trace how the business really runs.
Two design choices matter for the commercial story. First, unlike a data warehouse, which takes years of pipelines to fill and maintain, the Context Warehouse fills itself by learning from work already happening. Second, the platform is independent of any data warehouse, AI model, or application platform. Enterprises can swap models and tools without rebuilding how context is managed, and the product works with the agents teams already use, including through MCP.
The company claims the approach lets agents reason on signal instead of noise while cutting unnecessary retrieval and token consumption by up to 10x. In a market where AI operating costs are becoming a board-level concern, that number is the pitch.
“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.”
Competing Against Internal Builds
The most immediate competition is not another vendor. It is the internal teams at large enterprises already building context layers and company brains themselves. Modus does not dispute that those efforts can produce a working first version. Its argument targets what happens afterward.
“Building a context layer is not the hardest part,” said Tomer Mesika, CTO and co-founder of Modus. “Keeping it current is. Every change your business makes changes the context AI depends on. The real decision is no longer buy versus build. It is whether you want to own the ongoing cost of maintaining that understanding. We built the Context Warehouse so engineering teams can build what differentiates their business instead of maintaining the infrastructure underneath it.”
The governance design supports the enterprise sales motion. The platform learns from metadata and usage patterns across data warehouses, BI tools, pipelines, code repositories, documentation, and collaboration systems, without requiring organizations to centralize sensitive business data. Governance is enforced before context reaches the model, so every AI interaction receives only the information it is authorized to access while sensitive customer data stays inside the customer’s environment.
Founders with Relevant Scars
Shimoni was previously VP of Product at Lusha, where he saw that AI was only as useful as the business context behind the data. Mesika was Head of Architecture at Cyera, where he built infrastructure to classify, govern, and secure enterprise information at scale. Both arrived at the same conclusion from different directions: the systems enterprises rely on were never built for AI agents.
Traction and Trajectory
Modus is not entering the market cold. The platform is already deployed with enterprise customers across financial services, technology, and SaaS, where the company says it has improved AI accuracy, strengthened governance, accelerated response times, and reduced the cost of operating AI at scale.
The near-term product is accuracy, efficiency, and governance for AI agents. The longer-term vision is more proactive: a foundation that surfaces what matters, detects what changed, and helps teams move from trusted answers to trusted action. Whether Modus can define the category before larger platforms absorb the idea is the question the next few years will answer. Insight Partners has $10 million saying it can.
