onnxruntime/docs/ecosystem/index.md

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Ecosystem	See examples of how ONNX Runtime working end to end within the Azure AI and ML landscape and ecosystem	9	/docs/tutorials/ecosystem

ORT Ecosystem

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ONNX Runtime functions as part of an ecosystem of tools and platforms to deliver an end-to-end machine learning experience. Below are tutorials for some products that work with or integrate ONNX Runtime.

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Azure Container for PyTorch (ACPT)

• Azure Container for PyTorch (ACPT) docs{:target="_blank"}
• Azure Container for PyTorch (ACPT) - Azure Machine Learning{:target="_blank"}

Azure Machine Learning Services

• Azure Container Instance: BERT{:target="_blank"}
• Azure Kubernetes Services: FER+{:target="_blank"}
• Azure IoT Sedge (Intel UP2 device with OpenVINO){:target="_blank"}
• Automated Machine Learning{:target="_blank"}

Azure Custom Vision

• Export a Custom Vision model to ONNX format{:target="_blank"}
• Use a Custom Vision model with Windows Machine Learning{:target="_blank"}

Azure SQL Edge

• ML predictions in Azure SQL Edge and Azure SQL Managed Instance{:target="_blank"}

Azure Synapse Analytics

• ML predictions in Synapse SQL{:target="_blank"}

ML.NET

• Automated Machine Learning{:target="_blank"}
• Inference: Object detection{:target="_blank"}

NVIDIA Triton Inference Server

• ONNX Runtime backend for Triton{:target="_blank"}