Configuration

Web-server and public endpoint URL

You will need to host a publicly available web server that can process JSON over HTTPS. For security, we require the server to use HTTPS so any private information is encrypted end to end.

Authorization

The custom models service supports HTTP Basic Auth on your endpoint. You can configure username and password credentials for your custom model in your organization’s settings page.

If you are using multiple custom models, they will all share the same credentials. Therefore, all of your custom model endpoints must accept the same Basic Auth username and password.

Custom Model ID's

After setting up your custom model endpoint, contact your Alloy Solutions Architect with the endpoint URL. They will configure the custom model in our system & provide you with a custom model ID.

Custom Model Versioning

If you would like to test successive versions of your custom model, you can provide unique URLs to Alloy that invoke specific versions of your custom model. Alloy will then provide custom model ID's for each endpoint, allowing you to test different versions of your model within Workflow and Journey versions using Alloy's various testing tools.

Model Specifications

Input Payload Format

The custom model will receive service data attributes for services that have run prior to the Custom Models service in the workflow.

• The payload format consists of a serialized JSON string containing arrays of attribute_name / attribute_value pairs for each service. You may need to deserialize this string in your custom model code (ex: json.loads() in Python).
• If any data is passed to the evaluation under the entity's meta section, it will be included in the custom model payload
• Any output attributes calculated before running the custom model will be included in the payload under the Output Attributes section
  • It is important to make the custom model service dependent on the output attributes in some way to guarantee that they will be calculated before the custom model is run
• The Data Supplied section indicates whether certain PII was supplied or not (true/false).

Example:

{
    // Org name will be the organization name in the dashboard
    "[Org Name] Data Supplied":
    [
        {
            "attributeName": "birth_date",
            "attributeValue": "true"
        },
        {
            "attributeName": "name_last",
            "attributeValue": "true"
        },
        {
            "attributeName": "name_first",
            "attributeValue": "true"
        },
        ...
    ],
    "[Org Name] Meta":
    [
        {
            "attributeName": "income",
            "attributeValue": "100000"
        },
        ...
    ],
    "[Org Name] Output Attributes":
    [
        {
            "attributeName": "my_output_attribute",
            "attributeValue": "100"
        },
        ...
    ],
    // These sections depend on which services run prior to the custom model in the workflow
    "Experian":
    [
        {
            "attributeName": "ex",
            "attributeValue": "100"
        },
        ...
    ],
    "Lexis Nexis":
    [
        {
            "attributeName": "ex",
            "attributeValue": "100"
        },
        ...
    ],
    "Another workflow service":
    [
        {
            "attributeName": "ex",
            "attributeValue": "100"
        },
        ...
    ],
    ...
}

Output Format

Success

If successful, the custom model endpoint should return the following JSON response:

{
	"modelSuccess": true,
	"modelScore": number,
	"modelVersion": number,
	...Additional optional data...
}

Failure

If there is an error within the custom model code that can be handled, this can be returned to Alloy using the following JSON response:

{
	"modelSuccess": false
}