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| Step | Platform | Function | Comments |
|---|---|---|---|
| 1 | EdgeLake | Capture data from machines and infrastructure that generate data | EdgeLake is deployed on many Edge Nodes and hosts data from PLCs and sensors connected to each node |
| 2 | EdgeLake | Service the data to a Model Generation process on each Edge Node | Each Edge Node is deployed with EdgeLake + the code that generates the Sub-Model. |
| 3 | AI Code | Model Generation on each node creates a Sub-Model | Each edge node is queried using SQL by the Model Generation Process |
| 4 | EdgeLake | Makes all the Sub-Models available on a single node | Only Sub-Models are moved (not the data) |
| 5 | AI Code | A unified model is created | by combining all the Sub-Models |
| 6 | EdgeLake | The Unified Model is pushed to all the Edge Nodes | |
| 7 | EdgeLake | Service the data to the Inference Process on each Edge Node | |
| 8 | EdgeLake | The inference data from all edge nodes satisfies queries | Using EdgeLake's Virtual Data Lake - without the need to centralize the data |
| 9 | EdgeLake | The EdgeLake rule engine on each node can act and alert on the inference data | Machine optimization, setup and maintenance is done based on the inferenced data |
| 10 | PLCs/Sensors | New data is generated | back to step 1 |
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