Semarchy, a provider of Master Data Management, is evolving traditional MDM into Intelligent Data Products—delivering self-service Intelligent Data Products with built-in context, reasoning, and governance that can be consumed by teams, agents, and applications across the agentic enterprise.
According to Semarchy, organizations need more than mastered data connected to an AI model. They need the context to fully understand the business meaning and relationships behind the data, and the governance with explainability to know that it is accurate and trustworthy.
Intelligent Data Products, part of the Semarchy Data Platform, are built on three principles:
Design once, consume anywhere: Using Semarchy Data Platform's DataOps and AI Data Engineering capabilities, teams can build Intelligent Data Products in hours, not days. DataOps enables control and collaboration, while AI Data Engineering automates the generation of schemas, rules, and models ready for human review. This unique combination of capabilities is a dramatic accelerator of productivity, allowing organizations to design and build Intelligent Data Products in a fraction of the time it used to take, the company said.
Intelligence built-in, not layered on: Every Intelligent Data Product carries its mastered data together with the business context, relationships, explainability, and reasoning guidance needed to use it correctly. The richness of the semantic context can be used downstream, including analytics platforms and AI ecosystems to accurately leverage and present that data. The semantic intelligence can also be ingested into metadata management solutions, complementing their value in delivering context, said the vendor.
Persistent governance, enforced everywhere: Quality results, access rights, lineage, and certification history travel with every Intelligent Data Product, building trust through transparency. The same governance controls apply whether the consumer is a person, an agent or application.
Every Intelligent Data Product automatically creates its own MCP server. MCP is an open standard that lets AI assistants and agents securely discover and use AI-native enterprise tools and data. Through natural language questions, users and agents can understand an Intelligent Data Product's business purpose, entities, relationships, quality rules, and sensitive-data controls, then query and reason over the trusted data itself, without losing the governance that makes enterprise data dependable. Governance is persistent and enforced everywhere: quality, access rights, lineage, and certification history travel with every Data Product, and that transparency is what builds trust.
"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. "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."
Semarchy has also made it easier to discover and explore Intelligent Data Products. Business users, data stewards, data scientists and application developers can browse the Intelligent Data Products available to them, and review available metadata including their value, intended use, and data lineage to ensure fit for purpose.
With Intelligent Data Products, Semarchy is helping organizations make trusted data easier to discover, understand, and put to work, whether the user is a business analyst, data steward, application, copilot, or autonomous AI agent, said Semarchy.
For more information about this news, visit https://semarchy.com.