Semarchy, a recognized leader in the 2026 Gartner® Magic Quadrant™ for Master Data Management, announced a major evolution today. The company is moving beyond traditional MDM toward Intelligent Data Products. Consequently, this shift changes how enterprises share and consume data. Instead of simply distributing data and hoping teams interpret it correctly, Semarchy now delivers self-service Intelligent Data Products. These products include built-in context, reasoning, and governance. As a result, teams, AI agents, and applications across the agentic enterprise can use them directly.
“Enterprises are about to spend years engineering a context layer for AI. What we keep finding is that designing a data product IS building that context layer,” said Craig Gravina, CTO of Semarchy.
Furthermore, organizations need more than mastered data connected to an AI model. They also need context to understand business meaning and relationships. Additionally, governance and explainability ensure that data remains accurate and trustworthy. Therefore, Semarchy built its Intelligent Data Products around three core principles.
Design Once, Deploy Everywhere
First, teams can design once and consume anywhere. Using Semarchy Data Platform’s DataOps and AI Data Engineering tools, teams build Intelligent Data Products in hours. Meanwhile, DataOps enables collaboration and control across teams. Simultaneously, AI Data Engineering automates schema, rule, and model generation for human review. Thus, this combination dramatically accelerates productivity across the organization.
Second, intelligence comes built-in rather than layered on afterward. Every Intelligent Data Product carries mastered data alongside business context and reasoning guidance. Because context is embedded at design time, it cannot drift over time. In contrast, many MDM vendors add semantic context separately, often after the fact. Subsequently, this rich context strengthens analytics platforms and AI ecosystems downstream.
Third, governance stays persistent and enforced everywhere. Quality results, access rights, lineage, and certification history travel with every product. Moreover, identical governance controls apply whether the consumer is human, agent, or application.
Building Critical Infrastructure for Agentic Enterprises
Notably, every Intelligent Data Product automatically creates its own MCP server. MCP represents an open standard enabling AI agents to securely discover enterprise tools and data. Through natural language, users and agents can therefore understand a product’s purpose, entities, and quality rules. Meanwhile, governance remains intact throughout every interaction, which builds essential trust.
“Our customers have been doing it for years without calling it that, and we’re now making it available to agents. That’s why trusted data, delivered as an Intelligent Data Product, is the critical infrastructure of the agentic enterprise. The context is already there, already governed, and it can’t drift,” Gravina added.
Additionally, Semarchy simplified discovery and exploration for Intelligent Data Products. Business users, data stewards, and developers can now browse available products easily. They can review metadata, lineage, and intended use to confirm fit for purpose. Ultimately, this discovery layer makes trusted data accessible to both people and agents alike.
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News Source: Businesswire.com
