Frequent Asked Questions (FAQ)

What is Azure Machine Learning (Azure ML)?

Azure ML is Microsoft’s cloud-native platform for fully managing the ML lifecycle—training, deployment, monitoring, pipelines, AutoML, model registries, and responsible AI tooling—designed for data scientists and ML engineers.

What is Microsoft Foundry (formerly Azure AI Foundry, and Azure AI Studio before)?

Microsoft Foundry builds on Azure Machine Learning but is tailored specifically for generative AI and agent-based applications. It offers:

• A unified experience for building, evaluating, and deploying LLMs and multimodal agents.
• Access to a broad catalog of open-source and commercial frontier models—from Azure OpenAI, Hugging Face, Meta, DeepSeek, etc.
• Integrated tools like model evaluation leaderboards, prompt flows (for RAG), content safety, and agent orchestration.

More information can be found at What is Microsoft Foundry?.

What’s the difference between a Hub-based project and a Foundry (standalone) project ?

Feature	Hub-based project	Standalone Foundry project
Requires a Hub resource	✅ Yes—project is linked to a hub	❌ No—project created individually
Shared infrastructure (compute/quota)	✅ Yes	❌ No
Shared security/network settings	✅ Yes	❌ No
Shared resource connections	✅ Yes (e.g., models, storage)	❌ Per‑project only
Full Generative AI tooling (fine-tuning, evaluation, RAG, agent orchestration)	✅ Yes	⚠️ Limited support
Accessible from Azure ML Studio	✅ Yes	Limited/absent

Hub-based projects provide complete access to generative-AI features; standalone projects operate with limited capabilities. Open-model deployments are only accessible through Hub-based project for now.

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