People Intelligence

Use case

Turn partial lead records into full contact profiles for sales outreach, CRM enrichment, or lead qualification.

This endpoint is also available at /enrich-lead and /enrich-lead-async. Both paths are fully supported and functionally identical.

Endpoint

POST https://api.sixtyfour.ai/people-intelligence

API Reference

See the full request/response schema and parameters in the API Reference.

Pricing

See Credits & Pricing Guide for credit costs by tier.

Errors

For error responses (400, 403, 422, etc.), see Handling Errors.

Tiers

The tier parameter controls research depth and cost. To override the default, pass tier in the request body. See Sync usage for an example.

Tier	Description	Access
`micro`	Lightweight enrichment — returns up to 10 fields. Best for very high-volume lookups where only minimal data is needed.	All orgs
`low` (default)	Baseline tier — fast and cheap. Good for high-volume enrichment where you mostly need a name → email/LinkedIn mapping.	All orgs
`medium`	Deeper research with more sources and iterations. Better for hard-to-find contacts.	All orgs
`high`	OSINT-grade investigation — deeply recursive crawling across the open web, dark web, directories, proprietary sources. Designed for the hardest prospects, sensitive diligence, and investigative workflows.	Exclusive — access is granted case-by-case by our team. Contact sales to request.
`xhigh`	Maximum-depth OSINT investigation — extends `high` with additional research cycles for the hardest identity and diligence cases.	Exclusive — access is granted case-by-case by our team. Contact sales to request.

If tier is omitted, low is used. Requests with tier: "high" or tier: "xhigh" on an org without access return 403 — see Handling Errors.

Using the `struct` field

The struct field defines exactly what data you want back. Each key becomes a field in structured_data, and its value tells the agent what to find. You can pass either a plain-English description or an object with description and type:

{
  "struct": {
    "email": "The individual's email address",
    "github_url": {"description": "URL for their GitHub profile", "type": "str"}
  }
}

The agent uses these descriptions to guide its research. Be specific — "The individual's primary work email" returns better results than "email". For supported types, type resolution priority, and casting examples, see Struct & Type Casting.

Timeouts and parallelization

This endpoint performs deep research and is a long-running operation. Typical P95 runtime is about 5 minutes and can reach 10 minutes for complex leads. We are actively working on performance improvements.

Set client timeouts appropriately: If you call the sync endpoint, configure your HTTP client with a timeout of at least 15 minutes.
Prefer async in production: Use POST /people-intelligence-async and poll GET /job-status/{task_id}.
Parallelize for throughput: Submit multiple async jobs in parallel (bounded concurrency) rather than waiting for each to complete sequentially.

Understanding scores

Field	Meaning	Range
`confidence_score`	Global quality score — overall quality, consistency, and correctness of the returned data.	0–10

The findings field on the response is deprecated. It currently returns an empty list and will be removed in a future update.

Sync usage

Make a direct request and wait for the response. Enrichment can take several minutes depending on depth of research.

curl -X POST "https://api.sixtyfour.ai/people-intelligence" \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "lead_info": {
      "name": "Saarth Shah",
      "title": "CEO & Co-Founder @ Sixtyfour AI",
      "company": "Sixtyfour AI",
      "location": "San Francisco",
      "linkedin": "https://www.linkedin.com/in/saarthshah"
    },
    "struct": {
      "name": "The individual'\''s full name",
      "email": "The individual'\''s email address",
      "phone": "The individual'\''s phone number",
      "company": "The company the individual is associated with",
      "title": "The individual'\''s job title",
      "linkedin": "LinkedIn URL for the person",
      "website": "Company website URL",
      "location": "The individual'\''s location and/or company location",
      "industry": "Industry the person operates in",
      "github_url": "url for their github profile",
      "github_notes": "Take detailed notes on their github profile."
    },
    "tier": "medium"
  }'

import requests

response = requests.post(
    "https://api.sixtyfour.ai/people-intelligence",
    headers={
        "x-api-key": "YOUR_API_KEY",
        "Content-Type": "application/json"
    },
    json={
        "lead_info": {
            "name": "Saarth Shah",
            "title": "CEO & Co-Founder @ Sixtyfour AI",
            "company": "Sixtyfour AI",
            "location": "San Francisco",
            "linkedin": "https://www.linkedin.com/in/saarthshah"
        },
        "struct": {
            "name": "The individual's full name",
            "email": "The individual's email address",
            "phone": "The individual's phone number",
            "company": "The company the individual is associated with",
            "title": "The individual's job title",
            "linkedin": "LinkedIn URL for the person",
            "website": "Company website URL",
            "location": "The individual's location and/or company location",
            "industry": "Industry the person operates in",
            "github_url": "url for their github profile",
            "github_notes": "Take detailed notes on their github profile."
        },
        "tier": "medium"
    },
    timeout=900
)

response.raise_for_status()
results = response.json()

const response = await fetch("https://api.sixtyfour.ai/people-intelligence", {
  method: "POST",
  headers: {
    "x-api-key": "YOUR_API_KEY",
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    lead_info: {
      name: "Saarth Shah",
      title: "CEO & Co-Founder @ Sixtyfour AI",
      company: "Sixtyfour AI",
      location: "San Francisco",
      linkedin: "https://www.linkedin.com/in/saarthshah"
    },
    struct: {
      name: "The individual's full name",
      email: "The individual's email address",
      phone: "The individual's phone number",
      company: "The company the individual is associated with",
      title: "The individual's job title",
      linkedin: "LinkedIn URL for the person",
      website: "Company website URL",
      location: "The individual's location and/or company location",
      industry: "Industry the person operates in",
      github_url: "url for their github profile",
      github_notes: "Take detailed notes on their github profile."
    },
    tier: "medium"
  })
});

const results = await response.json();
console.log(results);

Async pattern

For production workflows, use /people-intelligence-async to submit a job and poll for results. This avoids long-lived HTTP connections during deep research runs. The flow is:

Submit — POST /people-intelligence-async with the same body as the sync endpoint. Response includes a task_id.
Poll — GET /job-status/{task_id} until status is completed, failed, or cancelled.
Read result — When completed, the full enrichment is in the result field.

The async start endpoint returns uppercase RUNNING. Subsequent /job-status/{task_id} calls return lowercase statuses. charge_amount is returned in cents, not credits.

Polling example

import requests
import time

response = requests.post(
    "https://api.sixtyfour.ai/people-intelligence-async",
    headers={"x-api-key": "YOUR_API_KEY", "Content-Type": "application/json"},
    json={
        "lead_info": {
            "name": "Saarth Shah",
            "title": "CEO & Co-Founder @ Sixtyfour AI",
            "company": "Sixtyfour AI",
            "location": "San Francisco",
            "linkedin": "https://www.linkedin.com/in/saarthshah"
        },
        "struct": {
            "name": "The individual's full name",
            "email": "The individual's email address",
            "phone": "The individual's phone number",
            "company": "The company the individual is associated with",
            "title": "The individual's job title",
            "linkedin": "LinkedIn URL for the person",
            "website": "Company website URL",
            "location": "The individual's location and/or company location",
            "industry": "Industry the person operates in"
        },
        "tier": "medium"
    }
)
response.raise_for_status()
task_id = response.json()["task_id"]

while True:
    status = requests.get(
        f"https://api.sixtyfour.ai/job-status/{task_id}",
        headers={"x-api-key": "YOUR_API_KEY"}
    ).json()

    if status["status"] == "completed":
        results = status["result"]
        break
    if status["status"] in ("failed", "cancelled"):
        raise RuntimeError(f"Job {status['status']}: {status.get('error', 'Unknown error')}")

    time.sleep(10)

async function runAsync() {
  const start = await fetch("https://api.sixtyfour.ai/people-intelligence-async", {
    method: "POST",
    headers: { "x-api-key": "YOUR_API_KEY", "Content-Type": "application/json" },
    body: JSON.stringify({
      lead_info: {
        name: "Saarth Shah",
        title: "CEO & Co-Founder @ Sixtyfour AI",
        company: "Sixtyfour AI",
        location: "San Francisco",
        linkedin: "https://www.linkedin.com/in/saarthshah"
      },
      struct: {
        name: "The individual's full name",
        email: "The individual's email address",
        phone: "The individual's phone number",
        company: "The company the individual is associated with",
        title: "The individual's job title",
        linkedin: "LinkedIn URL for the person",
        website: "Company website URL",
        location: "The individual's location and/or company location",
        industry: "Industry the person operates in"
      },
      tier: "medium"
    })
  });
  const { task_id } = await start.json();

  while (true) {
    const status = await (await fetch(
      `https://api.sixtyfour.ai/job-status/${task_id}`,
      { headers: { "x-api-key": "YOUR_API_KEY" } }
    )).json();

    if (status.status === "completed") return status.result;
    if (["failed", "cancelled"].includes(status.status)) {
      throw new Error(`Job ${status.status}: ${status.error || "Unknown error"}`);
    }
    await new Promise(r => setTimeout(r, 10000));
  }
}

Get Started

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Troubleshooting

Developer Tools

Use case

Endpoint

API Reference

Pricing

Errors

Tiers

Using the `struct` field

Timeouts and parallelization

Understanding scores

Sync usage

Async pattern

Polling example

​Use case

​Endpoint

API Reference

​Pricing

​Errors

​Tiers

​Using the struct field

​Timeouts and parallelization

​Understanding scores

​Sync usage

​Async pattern

​Polling example

Use case

Endpoint

Pricing

Errors

Tiers

Using the `struct` field

Timeouts and parallelization

Understanding scores

Sync usage

Async pattern

Polling example