Every enterprise is accumulating AI agents, skills, knowledge bases, and orchestration configurations at pace — and almost none of them can tell you what they have, who owns it, how sensitive it is, or what it costs. We solve that with ARIA: Asset Registry for Intelligent Agents.

ARIA is a four-layer reference architecture that brings the same rigor TOGAF applied to enterprise IT to the emerging discipline of AI asset management. The metamodel layer draws on the Open Agentic Schema Framework (OASF) — a community-driven, extensible taxonomy purpose-built for classifying AI primitives. The marketplace layer uses GitHub and OCI registries to version, validate, and publish AI assets through the same pull request workflows developers already know. The governance layer extends Microsoft Purview — sensitivity labels, DLP policies, and data lineage — into the AI asset domain, with inheritance rules that automatically propagate classifications through the full dependency graph. The distribution layer introduces a Catalog API that converts governed OCI artifacts into one-click installs for Claude Desktop, Cowork, and a web portal — making the governed path the easiest path for non-technical users.

In this session you will learn how to model agent-to-skill, agent-to-knowledge, and orchestration-to-agent relationships with governance implications baked in; how to build a GitHub-native AI marketplace with automated OASF schema validation and Purview synchronization on every merge; and how to deliver governed AI capabilities to business users without exposing them to container registries or CLI tooling. We will also cover AI FinOps — extending the OASF governance overlay with cost governance fields, per-asset budget enforcement middleware, and provider billing attribution across GitHub Models, Azure OpenAI, and others.

You will leave with a practical, implementable architecture and a working reference implementation in C# on Microsoft Agent Framework — ready to adapt for your own enterprise.

Audience: Enterprise architects, AI platform engineers, governance and compliance leads, developer platform teams.

Level: Intermediate to Advanced