Azure AI Foundry is Microsoft's platform for building AI applications and agents properly: one environment for the model catalogue, prompt engineering, retrieval, evaluation, tracing and deployment, wrapped in the enterprise controls Azure is trusted for. It is the difference between AI development happening on a governed platform and AI development happening on someone's corporate card.
Our Foundry builds run Azure OpenAI models as the default engine, deployed regionally for data residency and routed per workload for cost and capability. The platform itself is engineered like everything else we ship on Azure: landing-zone aligned, private endpoints and customer-managed keys where sovereignty demands, Entra identity throughout, and infrastructure as code from the first commit.
What separates a good Foundry estate from a demo environment is the operational layer. Evaluation pipelines with golden datasets and regression gates, prompt and response logging for audit, tracing on agentic workloads, and quota and cost governance per team. We build those in before the first use case ships, because retrofitting rigour after users arrive is twice the work at twice the risk.
Foundry is also where our cloud and AI practices meet. The platform work here underpins the RAG services, custom applications and multi-agent systems our AI practice delivers, and hosts them alongside whatever your own teams build. One factory, many products, shared governance.