AI Modeling
Connect Source
Learn how to connect and configure an AI/ML model as a source for use within the AI Squared platform.
Connecting an AI/ML source is the first step in activating AI within your business workflows. AI Squared allows you to seamlessly integrate your deployed model endpoints—from providers like SageMaker, Vertex AI, Databricks, or custom HTTP APIs.
This guide walks you through connecting a new model source.
📸 Placeholder for: Input schema editor screenshot
📸 Placeholder for: Output schema editor screenshot
Need help? Head over to our Support & FAQs section for troubleshooting tips or reach out via the in-app help widget.
Step 1: Select an AI/ML Source
- Navigate to AI Activation → AI Modeling → Connect Source
- Click on Add Source
- Choose your desired connector from the list:
- AWS SageMaker
- Google Vertex AI
- Databricks Model
- OpenAI Model Endpoint
- HTTP Model Source (Generic)
Step 2: Enter Endpoint Details
Each connector requires some basic configuration for successful integration.Required Fields
- Endpoint Name – A meaningful name for this model source
- Endpoint URL – The endpoint where the model is hosted
- Authentication Method – e.g., OAuth, API Key, Bearer Token
- Auth Header / Secret Key – If applicable
- Request Format – Structure expected by the model (e.g., JSON payload)
- Response Format – Format returned by the model (e.g., structured JSON with keys)
Step 3: Test Connection
Click Test Connection to validate that the model endpoint is reachable and returns a valid response.- Ensure all fields are correct
- The system will validate the endpoint and return a success or error message
Step 4: Define Input Schema
The input schema specifies the fields your model expects during inference.| Field | Description |
|---|---|
| Name | Key name expected by the model |
| Type | Data type: String, Integer, Float, Boolean |
| Value | Static or dynamic input value |
Step 5: Define Output Schema
The output schema ensures consistent mapping of the model’s response.| Field | Description |
|---|---|
| Field Name | Key name from the model response |
| Type | Data type: String, Integer, Float, Boolean |
Step 6: Save the Source
Click Save once configuration is complete. Your model source will now appear in the AI Modeling tab and can be used in downstream workflows such as Data Apps or visualizations. 📸 Placeholder for: Final save and confirmation screenNeed help? Head over to our Support & FAQs section for troubleshooting tips or reach out via the in-app help widget.