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