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Update Foundry Overview with new features and comparisons
Added new features and comparisons for Microsoft Foundry, including hosted agents, model router, and enterprise governance.
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- [Microsoft Foundry architecture](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/architecture?view=foundry-classic&utm_source=copilot.com)
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- [What is the Microsoft Foundry Control Plane?](https://learn.microsoft.com/en-us/azure/ai-foundry/control-plane/overview?view=foundry&utm_source=copilot.com)
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- [Comparing Content Understanding in Microsoft Foundry vs Content Understanding Studio](https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/foundry-vs-content-understanding-studio?utm_source=copilot.com)
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- [Foundry Agent Service at Ignite 2025: Simple to Build. Powerful to Deploy. Trusted to Operate.](https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/foundry-agent-service-at-ignite-2025-simple-to-build-powerful-to-deploy-trusted-/4469788)
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</details>
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> - Agent Centric: Designed around `AI agents and workflows rather than just models`
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> - Developer-Friendly: Simplifies `project setup, resource management, and SDK/API usage`
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`Classic = LLM sandbox`
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`Classic = LLM sandbox` <br/>
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`New = Agent platform with enterprise governance`
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| Aspect | Foundry (Classic) | Foundry (New) |
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| **Integration** | `Separate tools for models, apps, infra` → Developers had to stitch together SDKs and services. | `Unified under one platform (agents + models + tools)` → A cohesive environment where agents, models, and data connectors work seamlessly. |
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| **Evolution** | `Azure AI Foundry branding` → Focused on LLM experimentation within Azure. | `Microsoft Foundry rebrand (Ignite 2025)` → Signals the strategic pivot to enterprise AI agents and unified workflows. |
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## Key New Features (2025–2026)
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> `Microsoft Foundry is no longer just a model playground, it’s a unified agent platform that lets developers and enterprises`:
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- Build multi-agent systems
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- Orchestrate models across providers
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- Govern and monitor AI behavior
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- Deploy agents into real-world environments like Teams, web apps, and internal tools
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| Feature | Description | Key Benefits |
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|---------|-------------|--------------|
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| [Hosted Agents](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/concepts/hosted-agents?view=foundry&tabs=cli) | Build, test, and deploy agents without managing infrastructure. No need for Kubernetes or containers. Supports multi-agent orchestration with shared memory and tools. | Simplifies deployment, reduces infra overhead, enables complex agent ecosystems for enterprise workflows and internal copilots. |
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| [Model Router](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/model-router?view=foundry-classic#supported-underlying-models) | Routes requests across multiple models (OpenAI, Claude, Gemini, etc.). Automatically selects the best model for the task. Supports fallback and load balancing. | Optimizes performance and cost, ensures reliability, allows seamless switching between models without code changes. |
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| [BYO Model Gateway](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/ai-gateway?view=foundry) | Bring your own model (BYOM) from Hugging Face, Azure ML, or custom endpoints. Integrates with Foundry’s governance and observability stack. | Flexibility to use custom or proprietary models, hybrid cloud/on-prem strategies, unified monitoring and compliance. |
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| [One-Click Deployment to Microsoft 365](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/publish-copilot?view=foundry) | Deploy agents directly into Teams, Outlook, SharePoint, and other M365 apps. Includes low-code/no-code templates for internal copilots. Supports user identity, permissions, and organizational data access. | Rapid enterprise adoption, seamless integration with daily productivity tools, secure identity-aware deployments. |
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| [Built-in Observability](https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/observability-in-foundry-control-plane-empowering-developers-to-evaluate-and-opt/4471107) | Native tracing, telemetry, and evaluation dashboards. Human-in-the-loop feedback tools. Agent memory inspection and optimization tracking. | Improves reliability, enables debugging and optimization, ensures agents meet performance and compliance standards. Useful refs: [Exercise 04: Observe model utilization in Microsoft Foundry](https://microsoft.github.io/TechWorkshop-L300-AI-Apps-and-agents/docs/04_observability_ai_foundry/04_observability_ai_foundry.html), [Agent tracing overview (preview)](https://learn.microsoft.com/en-us/azure/ai-foundry/observability/concepts/trace-agent-concept?view=foundry), [Observability in generative AI](https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability?view=foundry-classic), [Continuously evaluate your AI agents (preview)](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/continuous-evaluation-agents?view=foundry-classic) |
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| [Enterprise Governance](https://learn.microsoft.com/en-us/azure/ai-foundry/control-plane/overview?view=foundry) | Identity management via Microsoft Entra ID. Policy enforcement, audit logging, and compliance controls. Role-based access and agent sandboxing. | Enterprise-grade security, compliance readiness, controlled access, and safe scaling across organizations. |
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> BYO Model Gateway:
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<img width="850" alt="image" src="https://github.com/user-attachments/assets/24ad6a0b-5de9-4cbf-a5ff-3c480aff6d8a" />
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From [Bring your own AI gateway to Azure AI Agent Service (preview)](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/ai-gateway?view=foundry)
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> Foundry Control Plane Core Functionalities:
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<img width="600" alt="image" src="https://github.com/user-attachments/assets/31dcc997-0eb0-424c-b843-dc58e3b89f7d" />
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From [What is the Microsoft Foundry Control Plane?](https://learn.microsoft.com/en-us/azure/ai-foundry/control-plane/overview?view=foundry)
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> Agent-Centric Architecture:
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| Component | Role |
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|-----------|------|
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| **Agent Framework** | Defines agent behavior, tools, memory, and orchestration |
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| **Hosted Agents** | Runs agents in managed environments |
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| **Model Router** | Chooses optimal model per task |
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| **Observability Stack** | Tracks agent decisions, performance, and feedback |
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| **Governance Layer** | Enforces policies, identity, and compliance |
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