Beyond Data Inventory: Catalogs to Context Engines as Decision Infrastructure

Enterprise data catalogs solved a critical problem.

They helped organizations discover data, understand ownership, establish governance, and improve trust. For most enterprises, those challenges remain far from solved, however. In fact, if you look at customer conversations today, the majority are still focused on finding data, improving data quality, documenting lineage, and increasing adoption of governance programs.

Now a new challenge is emerging.

AI agents, decision automation systems, and autonomous workflows require more than metadata to scale beyond handcrafted prompts and context-engineered solutions effectively. To simplify and scale trust in autonomous solutions, they require machine-readable context atop what data exists to explain what that data means, how it should be used, what constraints apply, and what outcomes matter.

This report argues that a new architectural layer is emerging between data and decisions: the enterprise context layer. In this report, enterprise context layer refers to the runtime layer that assembles business meaning, metadata, memory, operational state, policies, trust signals, and permitted actions so humans and machines can make governed decisions.

Although many vendors now describe their offerings as context platforms, context engines, or AI-ready governance solutions, the market hasn’t yet converged on what context actually means, where it should reside, or how it will be packaged and served. Constellation Research already sees vendors from data platforms, orchestration, observability, semantics, and enterprise application markets positioning themselves to own context. The next competitive battle is not over managing metadata. It is over assembling, governing, and activating context at runtime.

The organizations that meet this challenge will accelerate decision velocity beyond analytics-driven decision support, increase trust in AI, and create the foundation for scalable decision automation.