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Use Case

Enrich entire company data with additional information and find associated people for sales outreach, CRM enrichment, or lead qualification.

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Endpoint

POST https://api.sixtyfour.ai/enrich-company

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Request

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Headers

NameTypeRequiredDescription
x-api-keystringYesYour Sixtyfour API key
Content-TypestringYesMust be application/json

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Body

FieldTypeRequiredDescription
target_companyobjectYesCompany data to enrich
structobjectYesFields to collect
lead_structobjectNoCustom schema to define the structure of returned lead data
find_peoplebooleanNoWhether to find people associated with the company
full_org_chartbooleanNoWhether to retrieve the full organizational chart for the company
research_planstringNoOptional strategy describing how the agent should search for information
people_focus_promptstringNoDescription of people to find, typically includes the roles or responsibilities of the people you’re looking for
The struct field defines exactly what data you want back. Each key is a field name you want returned in structured_data, and its value is either a plain-English description (e.g., "Instagram url for the photography company") or an object with description and optional type (e.g., {"description": "Approximate employee count", "type": "int"}). The agent uses these descriptions to guide its research.

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find_people vs full_org_chart

  • find_people: Finds specific people associated with the company. Use people_focus_prompt to filter by role or seniority.
  • full_org_chart: Retrieves the complete organizational chart for the company. Use this when you need comprehensive coverage of all roles and reporting structure rather than targeted lead discovery.

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Research Plan vs People Focus Prompt

  • research_plan: Focuses on the methodology of finding data. Use this to guide the agent on where to look (e.g., “Check the ‘About Us’ page and LinkedIn Company People tab”).
  • people_focus_prompt: Focuses on the criteria for the people you want to find. Use this to filter by role, department, or seniority (e.g., “Find the VP of Marketing and the CTO”).

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Response

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Success Response (200)

Returns enriched company data including leads if requested. 
{
  "notes": "Pacific View Studios is a boutique photography company based in La Jolla, California. They specialize in luxury wedding photography, high-end portrait sessions, and commercial work for local businesses. The company has a strong social media presence and professional website. The business operates with a small, dedicated team of photographers and support staff.",
  "structured_data": {
    "company_name": "Pacific View Studios",
    "address": "1234 Ocean View Dr, La Jolla, CA 92037",
    "phone_number": "+16195551234",
    "website": "https://pacificview.studio",
    "num_employees": "5-10 employees",
    "instagram_url": "https://www.instagram.com/pacificview.studio",
    "leads": [
      {
        "name": "Sarah Chen",
        "email": "sarah@pacificview.studio",
        "title": "Creative Director & Lead Photographer",
        "phone": "+16195551234",
        "score": 9,
        "linkedin": "https://www.linkedin.com/in/sarah-chen-photography"
      },
      {
        "name": "Michael Rodriguez",
        "email": "michael@pacificview.studio",
        "title": "Office Manager",
        "phone": "+16195551234",
        "score": 8,
        "linkedin": "https://www.linkedin.com/in/michael-rodriguez-pvs"
      }
    ]
  },
  "findings": [],
  "references": {
    "https://pacificview.studio": "Official company website with services and portfolio",
    "https://www.instagram.com/pacificview.studio": "Company Instagram profile showing recent work",
    "https://www.linkedin.com/in/sarah-chen-photography": "LinkedIn profile of the Creative Director",
    "https://www.linkedin.com/in/michael-rodriguez-pvs": "LinkedIn profile of the Office Manager"
  },
  "confidence_score": 9.5
}
The findings field is deprecated. It currently returns an empty list and will be removed in a future update.

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Score Definitions

FieldDescriptionRange
confidence_scoreGlobal Quality Score: Measures the overall quality, consistency, and correctness of the returned data.0-10
scoreRelevance Score: Measures the likelihood of the person to match the prompt or be helpful (returned per lead).0-10

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Error Response (400)

{
  "error": "Bad Request",
  "message": "Invalid company data"
}

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Sync Usage

Make a direct request and wait for the response. This is the simplest approach, but note that enrichment can take several minutes depending on depth of research. 
curl -X POST "https://api.sixtyfour.ai/enrich-company" \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "target_company": {
      "company_name": "Pacific View Studios",
      "address": "1234 Ocean View Dr, La Jolla, CA 92037",
      "phone_number": "+16195551234",
      "website": "https://pacificview.studio"
    },
    "struct": {
      "instagram_url": "Instagram url for the photography company",
      "num_employees": "How many employees work there"
    },
    "lead_struct": {
      "name": "Full name of the person",
      "email": "Work email address",
      "title": "Job title",
      "linkedin": "LinkedIn profile URL"
    },
    "find_people": true,
    "research_plan": "Check their website, online profiles, and linkedin for the people",
    "people_focus_prompt": "Find me the owners of the company and the office manager"
  }'

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Async Usage

For production workflows, use the async endpoint to submit a job and retrieve results later. This avoids long-lived HTTP connections.

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Start Async Job

POST https://api.sixtyfour.ai/enrich-company-async
The request body is identical to the sync endpoint. Response: 
{
  "task_id": "bdd69815-a1c0-480d-bfa5-d5fbb9745893",
  "status": "pending"
}

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Check Job Status

GET https://api.sixtyfour.ai/job-status/{task_id}
Pending/Processing: 
{
  "status": "pending",
  "processed_items": 0,
  "total_items": 0,
  "task_type": "enrich_company"
}
Completed: 
{
  "status": "completed",
  "result": {
    "notes": "Pacific View Studios is a boutique photography company based in La Jolla, California...",
    "structured_data": {
      "company_name": "Pacific View Studios",
      "address": "1234 Ocean View Dr, La Jolla, CA 92037",
      "phone_number": "+16195551234",
      "website": "https://pacificview.studio",
      "num_employees": "5-10 employees",
      "instagram_url": "https://www.instagram.com/pacificview.studio",
      "leads": [
        {
          "name": "Sarah Chen",
          "email": "sarah@pacificview.studio",
          "title": "Creative Director & Lead Photographer",
          "phone": "+16195551234",
          "score": 9,
          "linkedin": "https://www.linkedin.com/in/sarah-chen-photography"
        },
        {
          "name": "Michael Rodriguez",
          "email": "michael@pacificview.studio",
          "title": "Office Manager",
          "phone": "+16195551234",
          "score": 8,
          "linkedin": "https://www.linkedin.com/in/michael-rodriguez-pvs"
        }
      ]
    },
    "findings": [],
    "references": {
      "https://pacificview.studio": "Official company website with services and portfolio",
      "https://www.instagram.com/pacificview.studio": "Company Instagram profile showing recent work",
      "https://www.linkedin.com/in/sarah-chen-photography": "LinkedIn profile of the Creative Director",
      "https://www.linkedin.com/in/michael-rodriguez-pvs": "LinkedIn profile of the Office Manager"
    },
    "confidence_score": 9.5
  },
  "task_type": "enrich_company"
}

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Example Async Usage

import requests
import time

# Start async job
response = requests.post(
    "https://api.sixtyfour.ai/enrich-company-async",
    headers={
        "x-api-key": "YOUR_API_KEY",
        "Content-Type": "application/json"
    },
    json={
        "target_company": {
            "company_name": "Pacific View Studios",
            "website": "https://pacificview.studio"
        },
        "struct": {
            "instagram_url": "Instagram url for the photography company",
            "num_employees": "How many employees work there"
        },
        "find_people": True
    }
)

response.raise_for_status()
task_info = response.json()
task_id = task_info["task_id"]

# Poll for results
while True:
    status_response = requests.get(
        f"https://api.sixtyfour.ai/job-status/{task_id}",
        headers={"x-api-key": "YOUR_API_KEY"}
    )
    status_response.raise_for_status()

    status_data = status_response.json()

    if status_data["status"] == "completed":
        results = status_data["result"]
        break
    elif status_data["status"] == "failed":
        print(f"Job failed: {status_data.get('error', 'Unknown error')}")
        break

    time.sleep(10)  # Wait 10 seconds before checking again

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Type Casting

The API automatically handles type casting for structured data output with intelligent type preservation and conversion.

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Type Priority Order

  1. Explicit Type Definitions (Highest Priority) - Specified in struct field definitions
  2. Original Input Types - Types from target_company when not explicitly overridden
  3. Inferred Types - From example values in struct
  4. Default to String (Lowest Priority)

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Supported Types

TypeExample Values
"str" or "string""Pacific View Studios"
"int" or "integer"50, 1000
"float"95.5, 3.14
"bool" or "boolean"true, false
"list"["item1", "item2"]
"list[str]"["item1", "item2"]
"list[int]"[1, 2, 3]
"list[float]"[1.5, 2.7, 3.14]
"dict"{"key": "value"}

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Examples

Type Override: 
{
  "target_company": {"num_employees": 25, "is_public": true},
  "struct": {
    "num_employees": {"type": "str"},  // Overrides original int type
    "industry": "Primary business sector"  // New field as string
  }
}
// Output: {"num_employees": "25", "is_public": true, "industry": "Photography"}
Explicit Type Definition: 
{
  "struct": {
    "employee_count": {"description": "Number of employees", "type": "int"},
    "is_verified": {"description": "Verification status", "type": "bool"}
  }
}
// Output: {"employee_count": 25, "is_verified": true}
Type Inference from Values: 
{
  "struct": {
    "rating": 4.5,        // Inferred as float
    "is_remote": false,   // Inferred as bool
    "founded_year": 2020  // Inferred as int
  }
}