Skip to main content
This walkthrough shows how to take a list of leads (names + companies) and enrich them with contact information using the Databar API.

​
What you will do

  1. Search for an enrichment that finds emails by name and company
  2. Run it in bulk for your entire list
  3. Poll for results

​
Prerequisites

  • A Databar API key (get one here)
  • A list of leads with at least a name and company

​
Step 1: Find the right enrichment

Search for enrichments that match your use case: 
curl "https://api.databar.ai/v1/enrichments/?q=email%20finder" \
  -H "x-apikey: YOUR_API_KEY"
Look through the results for an enrichment that accepts name and company (or similar) as input parameters. Note the id and check the price field.
Use Get enrichment details to see all required and optional parameters before running.

​
Step 2: Run in bulk

Once you have the enrichment ID, run it against your full list: 
curl -X POST "https://api.databar.ai/v1/enrichments/ENRICHMENT_ID/bulk-run" \
  -H "x-apikey: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "params": [
      {"full_name": "Sarah Chen", "company": "Stripe"},
      {"full_name": "James Lee", "company": "Notion"},
      {"full_name": "Maria Garcia", "company": "Figma"}
    ]
  }'
You will receive a task_id in the response.

​
Step 3: Poll for results

Check the task status until it completes: 
curl "https://api.databar.ai/v1/tasks/YOUR_TASK_ID" \
  -H "x-apikey: YOUR_API_KEY"
When status is completed, the data field contains your enriched results with emails, phone numbers, LinkedIn profiles, and other fields depending on the provider.
Task data is stored for 24 hours. Make sure to retrieve and save your results before they expire.

​
With the Python SDK

The SDK handles polling automatically: 
from databar import DatabarClient

client = DatabarClient()

leads = [
    {"full_name": "Sarah Chen", "company": "Stripe"},
    {"full_name": "James Lee", "company": "Notion"},
    {"full_name": "Maria Garcia", "company": "Figma"},
]

results = client.run_enrichment_bulk_sync(ENRICHMENT_ID, leads)
for r in results:
    print(r)

​
Next steps

Waterfall email finder

Maximize email coverage by trying multiple providers.

Table enrichment pipeline

Store and enrich data in a Databar table for ongoing workflows.