Bring richer insights to your AI workflows by connecting external APIs like Explorium to GPTfy. This guide walks you through how to set up and use a custom API Data Source that enriches your Salesforce records with firmographic data based on the website field—and makes it available for AI processing in GPTfy.
Why Use an API Data Source?
Your Salesforce data only tells part of the story. With GPTfy’s API Data Source capability, you can:
- Enrich records with external firmographic or demographic data
- Customize which fields are sent and received
- Feed combined insights into GPTfy prompts and workflows
- Support use cases like whitespace analysis, summarization, and insight generation
What You’ll Need
Before getting started, ensure you have:
- An External Credential and Named Credential for the external API (e.g., Explorium)
- A Custom Apex Connector Class that implements ccai.AIDataSourceInterface
- A Salesforce Record (like an Account) that includes a Website field
- Access to the GPTfy Cockpit
High-Level Process Flow
- Configure authentication using Named Credential
- Implement the connector class to call the API
- Activate the API Data Source in GPTfy
- Create context mapping for a Salesforce object (e.g. Account)
- Create a prompt that uses this data
- Test the integration on a sample record
Now, let’s connect to the API Data Source ( Explorium ) by following these steps:
Step-by-Step Guide (Using Explorium)
Step 1: Add a Named Credential
- Open your GPTfy Cockpit
- Navigate to Manage Configuration > API Data Source
- Click to Add New Named Credential
- Set the name as Explorium
- Choose Explorium as the data source
- Specify your custom connector class name, such as SampleDataSourceClass
Step 2: Save and Validate
Click Save
Refresh the page to ensure your settings and connector class are properly registered
Step 3: Activate the Data Source
Locate the data source you just added
Click Activate to enable this connector
Step 4: Set Up Data Context Mapping
Go to Data Context Mapping
Choose your target object (e.g., Account)
Add a mapping for the Website field
Select Explorium as the connected API Data Source
This allows GPTfy to extract the website from the record and use it in your connector class.
Step 2: Save and Validate
Click Save
Refresh the page to ensure your settings and connector class are properly registered
Step 3: Activate Data Source
Locate the data source you just added
Click Activate to enable this connector
Step 4: Set Up Data Context Mapping
Go to Data Context Mapping
Choose your target object (e.g., Account)
Add a mapping for the Website field
Select Explorium as the connected API Data Source
This allows GPTfy to extract the website from the record and use it in your connector class.
Step 5: Create Your Prompt
Now, build a prompt that leverages the enriched data:
Navigate to Prompt Configuration
Create a new prompt that references the Account object
When the prompt runs, GPTfy will:
- Fetch the website
- Use Explorium to enrich the data
- Pass the enriched data and prompt to the AI model
Step 6: Test It on a Record
Open an Account record
Add a valid business website (e.g., www.nyiax.com)
Run your configured GPTfy prompt
GPTfy fetches enrichment from Explorium and returns AI-driven insights
Note: Use a real, verified company website to get meaningful results from Explorium.
What’s Happening Behind the Scenes
You run a prompt on an Account
GPTfy extracts the website field
Your custom connector sends it to Explorium
Explorium returns firmographic or business info
GPTfy merges that data with Salesforce data
AI uses the combined dataset to answer your prompt
Use cases include
Whitespace analysis
Summary Generation
Intelligent account research
Triggering automation based on returned data
Sample Connector Class
Note: The sample code here is provided ‘as-is’ for reference and informational purposes only.
You can refer to this to understand how a similar connection can be made with other API Data Sources.
Code
global class SampleDataSourceClass implements ccai.AIDataSourceInterface{
public String getExternalData(ccai__AI_Data_Source__c dataSource, String extractedData){
Map<String, Object> mainMap = (Map<String, Object>)JSON.deserializeUntyped(extractedData);
if(mainMap.containsKey(‘Website’) && mainMap.get(‘Website’) != null){ //getting the website from the account extracted data.
String apiData = SampleDataSourceClass.connectToExplorium(String.valueOf(mainMap.get(‘Website’)), dataSource); //calling the explorium to get the information using the website.
if(String.isNotBlank(apiData)){
List<Object> apiDataList = (List<Object>)JSON.deserializeUntyped(apiData); //parsing the data returned from Explorium.
if(apiDataList != null && !apiDataList.isEmpty()){
Map<String, Object> apiDataMap = (Map<String,Object>)apiDataList.get(0);
for(String key : apiDataMap.keySet()){
mainMap.put(key, String.valueOf(apiDataMap.get(key))); //adding the description returned from Explorium to AI for processing.
}
}
}
}
return JSON.serialize(mainMap);
}
public static String connectToExplorium(String sourceUrl , ccai__AI_Data_Source__c dataSource){
HttpRequest request = new HttpRequest();
request.setEndpoint(‘callout:’+ dataSource.ccai__Named_Credential__c); //create a named credential for the external system you are calling
request.setMethod(‘POST’);
request.setHeader(‘accept’, ‘application/json’);
request.setHeader(‘content-type’, ‘application/json’);
request.setTimeOut(120000);
List<requestBody> lstObj = new List<requestBody>();
lstObj.add(new requestBody(sourceUrl)); //passing the website URL
String body = JSON.serialize(lstObj);
request.setBody(body);
Http http = new Http();
HttpResponse response = http.send(request);
System.debug(‘body: ‘+response.getBody());
System.debug(‘status: ‘+response.getStatus());
System.debug(‘statusCode: ‘+response.getStatusCode());
return response.getBody();
}
public class requestBody{
public String url {get; set;}
public requestBody(String url){
this.url = url;
}
}
}