Modus Emerges From Stealth With $10M Seed Led by Insight Partners

New York, USA, July 29th, 2026, FinanceWire

As enterprises move beyond AI experimentation and begin deploying agents in production, a new infrastructure challenge is emerging: giving AI systems enough business context to produce reliable results without overwhelming them with irrelevant information.

Modus is entering that market with a new approach. According to Axios, the Tel Aviv-based 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 is introducing what it calls the Context Warehouse, an infrastructure layer designed to address what Modus describes as the "Context Gap" between the information AI systems can access and their understanding of how a business actually operates.

The Problem With Too Much Context

Enterprise AI systems can already connect to a wide range of information sources, including data warehouses, business intelligence tools, documents, tickets, code repositories, and collaboration platforms. But access to information does not necessarily translate into an understanding of how that information should be interpreted.

AI agents may not know which business definitions are trusted, which dashboards teams actually rely on, why a metric changed, or which business logic should take precedence. As enterprises connect AI to more systems, the result can be increased complexity, slower responses, higher costs, and less reliable outputs.

Modus argues that the core issue is not necessarily a lack of context, but an excess of irrelevant context. Agents can over-fetch information, repeatedly query enterprise systems, and consume unnecessary tokens because they lack an understanding of which information matters for a particular task.

"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."

Building a System of Understanding

Modus sees the Context Warehouse as an equivalent to the role data warehouses play for enterprise data. Instead of serving as a central repository for information, however, the platform is designed to continuously learn how an organization actually works and provide AI interactions with only the context relevant to their needs.

The system learns from metadata and usage patterns across data warehouses, BI tools, pipelines, code repositories, documentation, and collaboration systems. It also incorporates the "tribal knowledge" that emerges through real business activity, including recurring analyst queries, frequently used dashboards, decision threads, and other signals that reveal how an organization operates.

According to Modus, this approach allows context to be earned through real usage rather than manually documented once and left to become outdated. The company says the platform can reduce unnecessary retrieval and token consumption by up to 10x.

The Context Warehouse operates independently of any specific data warehouse, AI model, or application platform. It also works with the agents teams already use, including through MCP, while allowing companies to avoid centralizing sensitive business data.

The Challenge of Maintaining Context

The founders' experience shaped Modus' focus on the infrastructure required to keep enterprise context current. Daniel Shimoni previously served as VP of Product at Lusha, while Tomer Mesika was Head of Architecture at Cyera, where he built infrastructure for classifying, governing, and securing enterprise information at scale.

The company argues that maintaining an accurate understanding of a business may be more difficult than building an initial context layer. As organizations change, the information AI systems depend on changes with them.

"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."

Modus says its platform is already deployed with enterprise customers across financial services, technology, and SaaS, helping organizations improve AI accuracy, strengthen governance, accelerate response times, and reduce the cost of operating AI at scale.

For Insight Partners, the company represents an opportunity to establish a new infrastructure category as AI becomes more deeply embedded in enterprise operations.

"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 company's longer-term vision extends beyond improving the accuracy and efficiency of today's AI agents. Modus believes that a continuously maintained understanding of enterprise operations could eventually enable AI systems to surface important developments, identify what has changed, and help organizations move from trusted answers toward trusted action.

Contact