Canonical capability · ai-ml
Machine Learning & AI
Train, deploy, and run inference against ML models.
12 capabilities
11 providers
About this category
Capabilities for ML/AI services — model training, inference endpoints, embeddings, fine-tuning, batch prediction. Includes managed model APIs (LLMs, vision, speech) and ML-platform tooling.
Common operations
- invoke-model
- list-models
- create-model
- run-inference
Implementations
| Provider | Capability | Operations | Tools | APIs Consumed |
|---|---|---|---|---|
| Advanced Micro Devices | AMD AI GPU Computing | 4 | 8 | 0 |
| AIMLAPI | AIMLAPI AI Model Operations | 4 | 4 | 0 |
| Amazon Neptune | Amazon Neptune Analytics and Machine Learning | 2 | 4 | 0 |
| Amazon Polly | Amazon Polly Text-to-Speech | 6 | 7 | 0 |
| Amazon SageMaker | Amazon SageMaker ML Lifecycle Management | 8 | 10 | 0 |
| Claude | Claude AI Messaging | 8 | 10 | 0 |
| Cloudflare | Cloudflare AI and ML | 4 | 15 | 0 |
| Hugging Face | Hugging Face Deployment and Operations | 12 | 14 | 0 |
| Hugging Face | Hugging Face Model Inference | 9 | 25 | 0 |
| Microsoft Azure | Azure AI and Cognitive Services | 4 | 11 | 0 |
| SAP | SAP Enterprise Business Operations | 19 | 30 | 0 |
| Snowflake | Snowflake Cortex AI | 6 | 20 | 0 |