#
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.

Update on GitHub