Azure AI Foundry Enterprise AI Agents

Azure AI Foundry, now branded Microsoft Foundry, is Microsoft’s platform for building, running, and governing AI agents at enterprise scale. It gives developers a managed runtime, access to more than 11,000 models, tools that connect agents to business systems, and the identity and governance controls IT needs. This guide explains what Foundry is, how the Agent Service works, how governance is enforced, what it costs, and how Indian enterprises should start. 

Azure AI Foundry is where most enterprise AI agent projects will either succeed or stall. Building a demo agent is easy. Running one in production, with identity, security, cost control, and an audit trail, is the hard part. Foundry exists to close that gap. 

First, a naming point that causes real confusion. Microsoft has consolidated the brand, and the platform is now widely called Microsoft Foundry, while Azure AI Foundry remains the name many teams still search for. They are the same platform. Microsoft describes it as a unified platform to build, ground, and govern AI apps and agents that understand your business context, bringing the full agent lifecycle together with consistent security, compliance, and policy controls. 

That governance emphasis is deliberate. At Microsoft Build 2026, Microsoft positioned Foundry as the place where AI agents move from experiments to production systems, shipping runtime, tools, memory, grounding, observability, and governance rather than just new model endpoints. 

This guide keeps it practical. You will learn what Azure AI Foundry is, how the Agent Service works, how governance and identity are enforced, what it costs, and how to start. No deep AI background needed. 

What Is Azure AI Foundry? 

Azure AI Foundry, now called Microsoft Foundry, is Microsoft’s enterprise platform for building, deploying, and governing AI agents and AI applications on Azure. It brings together a model catalog, a managed runtime, tools that connect agents to business data, and the security and policy controls enterprises need to run agents in production. 

Think of it as the factory floor for enterprise AI. A chatbot only generates text. An agent does work. Microsoft defines an agent as an AI application that reasons about requests and takes autonomous actions, calling tools, accessing external data, and making decisions across multiple steps. Some agents run with no chat interface at all, working in the background and triggered by system events. 

Scale tells you this is not a niche product. Microsoft reports that Foundry is used by developers at more than 80,000 enterprises, including 80 percent of Fortune 500 companies. For Indian enterprises already running Azure cloud services, Foundry is the natural place to build agents rather than stitching together separate AI tools. 

How Does the Foundry Agent Service Work? 

The Foundry Agent Service is a managed platform for building, deploying, and scaling AI agents. You choose a model, write instructions, attach tools, and Foundry runs the agent for you, handling conversation state, tool calls, safety checks, identity, and observability. You never manage the infrastructure underneath. 

Microsoft describes it as a managed platform that works with any framework and any supported model, using the Responses API as a single-entry point. There are two main ways to build. 

Prompt agents are the simple path. You author the agent in the Foundry portal or through an SDK, and Foundry runs it. There is no application code to maintain, no compute to pay for, and no containers to optimize, scale, or patch. 

Hosted agents are the developer path. You write agent code with your preferred framework, such as Microsoft Agent Framework, LangGraph, or the OpenAI Agents SDK, package it as a container, and let Foundry run it with a managed endpoint, scaling, identity, and observability built in. 

There is also a third route that avoids a rewrite. If you already have agent code running elsewhere, you can call the Responses API from your existing process to get Foundry models and platform tools without moving the code. That matters when you already have something working and simply need enterprise controls around it. 

How Do Agents Connect to Enterprise Data and Tools? 

Agents are only as useful as the systems they can reach. Foundry connects agents to business data and actions through tools, connectors, and the open Model Context Protocol standard, so an agent can search documents, query databases, and trigger real actions in your systems. 

The integration surface is wide. Microsoft states that Foundry agents can act across more than 1,400 prebuilt connections to business systems including SAP, Salesforce, and Dynamics 365, and can be extended with custom tools through MCP. For an Indian manufacturer running SAP, that means an agent can work against the ERP without a custom integration project. 

Grounding is handled by a dedicated knowledge layer. Foundry agents tap Foundry IQ, which unifies Work IQ, Fabric IQ, Azure SQL, and File Search behind a single retrieval endpoint. In plain terms, the agent gets your organization’s real context instead of guessing. 

Tool sprawl is managed too. Foundry’s Toolbox lets you define a curated set of tools once, manage them centrally, and expose them through a single endpoint, with tool search selecting the right tools per task rather than surfacing every tool to the model. That keeps agents focused and reduces the chance of an agent reaching for something it should not. 

How Is Governance and Identity Handled? 

Governance is the reason Foundry exists as a platform rather than a toolkit. Every agent runs with a managed identity through Microsoft Entra Agent ID, so IT applies the same access rules to agents that it applies to people. On top of that, Foundry adds tracing, evaluation, guardrails, and observability. 

Identity comes first. In Foundry you assign Microsoft Entra Agent IDs for centralized identity and policy enforcement, then test and publish with governance built in. This is the practical answer to the non human identity problem. An agent is a real identity with real access, so it needs least privilege, a named owner, and regular review. Strong identity and access management is the foundation everything else rests on. 

Network isolation is available for sensitive workloads. Teams can run agents with private networking options, including bring-your-own virtual network with no public egress. For BFSI and healthcare enterprises in India facing data residency and DPDP obligations, that matters more than any feature demo. 

Oversight is continuous, not a one-off review. Foundry lets teams monitor quality, cost, and safety with dashboards, tracing, red teaming, and built-in guardrails. Independent coverage of Build 2026 notes that Microsoft added trust and evaluation tooling including ASSERT, the Agent Control Specification, guardrail setup, and Agent ROI tooling to help teams govern agents during development, not just after deployment. 

And agents that reach into Microsoft 365 stay accountable. Foundry agents published into Teams or Copilot are governed centrally, with every action attributable, auditable, and governed through Agent 365 in the Microsoft Admin Center. Our guide on AI governance for Indian enterprises covers the wider accountability picture. 

What Does Azure AI Foundry Cost? 

There is no flat platform license. Microsoft states that Foundry Agent Service pricing is based on the individual models and tools you use. You pay for what an agent consumes, so cost tracks usage rather than headcount. 

That has two practical consequences for budgeting. First, a chatty agent that runs constantly costs far more than one triggered a few times a day. Task scope and trigger frequency drive your bill. Second, because Foundry offers access to more than 11,000 models spanning OpenAI, Anthropic, Meta, Google, and open-source families, you can route simple tasks to smaller, cheaper models and reserve expensive reasoning models for work that genuinely needs them. 

Model choice is the single biggest cost lever most teams ignore. Set budgets and monitor consumption from day one, because agent costs behave like cloud costs. They creep quietly until someone looks. 

How Should Indian Enterprises Get Started? 

Start narrow and prove value before you scale. Pick one workflow with a clear, measurable outcome, build a single agent, govern it properly, and measure the time saved. Broad rollouts before governance is in place are exactly where these projects stall. 

A practical sequence works well. Fix identity hygiene in Entra first, since agents inherit those controls. Then pick a use case where the work is repetitive and success is obvious, such as support triage or invoice matching. Ground the agent in real data rather than letting it guess. And turn on tracing and evaluation before go-live, not after an incident. 

Consider a BFSI firm in Mumbai. It builds a single agent to summarize customer complaints and route them to the right team. The agent gets its own Entra Agent ID, runs inside a private network with no public egress, and every action is traced. Once accuracy is proven and cost is understood, the firm adds a second agent. That is how agent programs scale safely. 

The pattern holds across industries: govern first, then grow. Embee Software helps Indian enterprises design that path through our managed IT services and cloud practice. 

Conclusion 

Azure AI Foundry, now Microsoft Foundry, is the platform that takes AI agents from demo to production. It gives developers a managed runtime, a vast model catalog, and deep connections into business systems. Just as importantly, it gives IT the identity, guardrails, and observability needed to trust what those agents actually do. 

The first step is not building an agent. It is deciding how you will govern one. Fix your identity foundation, choose a narrow first use case, and turn on tracing before you scale.

As a Microsoft Frontier Partner, Embee Software helps Indian enterprises assess AI readiness, build their first governed agents on Azure, and keep the cost under control as they grow. Book a free AI readiness assessment with our team to get started.