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 the Context Warehouse continuously learns from this activity and composes only the relevant context required for each AI interaction. The company says this can reduce unnecessary retrieval and token consumption by up to 10x, allowing agents to reason on relevant information rather than excessive data.

Built to Work Across the Enterprise Stack

The Context Warehouse is designed to operate independently of any specific data warehouse, AI model, or application platform. That approach is intended to let enterprises adopt new models and tools without rebuilding the way they manage context.

The platform also works with the agents teams already use, including through MCP. Modus says organizations do not need to centralize sensitive business data because the system learns from metadata and usage patterns, while sensitive customer data remains inside the customer's environment.

Governance is another part of the architecture. According to Modus, governance is enforced before context reaches the model, ensuring that AI interactions receive only information they are authorized to access.

The company was founded by Daniel Shimoni, former VP of Product at Lusha, and Tomer Mesika, former Head of Architecture at Cyera, where he built infrastructure to classify, govern, and secure enterprise information at scale. Their experience led them to a shared realization that the systems enterprises depend on were not built for AI agents.

The Cost of Building It Yourself

Modus is also targeting enterprises that have already begun creating their own context layers and company brains. The company's argument is that the biggest challenge may not be building an initial system, but keeping it accurate as the organization changes.

"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 the Context Warehouse is already deployed with enterprise customers across financial services, technology, and SaaS. According to the company, those organizations have used the platform to improve AI accuracy, strengthen governance, accelerate response times, and reduce the cost of operating AI at scale.

For Insight Partners, the investment reflects the view that AI's transition into production will create demand for a new category of enterprise infrastructure.

"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."

Modus' current focus is helping organizations deploy AI agents that are more accurate, efficient, secure, and easier to scale. Over time, the company believes the same continuously maintained understanding could support AI that does more than answer questions—surfacing what matters, detecting what changed, and helping enterprises move from trusted answers to trusted action.

This story was published on HackerNoon under our Business Blogging Program