# People Intelligence — AI-Powered Contact Research (`fortunate_favorite/people-intelligence`) Actor

Given a name and company, returns AI-analyzed contact intelligence: title, seniority, department, likely email formats, and confidence score. The natural complement to Company Intelligence. Pay only per successful result at $0.12/person — no subscription needed.

- **URL**: https://apify.com/fortunate\_favorite/people-intelligence.md
- **Developed by:** [Hampus](https://apify.com/fortunate_favorite) (community)
- **Categories:** AI, Lead generation, MCP servers
- **Stats:** 8 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $120.00 / 1,000 person analyses

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## People Intelligence — Apify Actor

**Name + company → structured contact intelligence. $0.10/person.**

> The natural complement to [Company Intelligence](https://apify.com/fortunate_favorite/company-intelligence). Same buyers, adjacent need: "I know the company — now who do I contact?"

***

### The Zero-Code Enrichment Pipeline (Zapier)

The most powerful use case requires zero engineering:

1. **New lead enters Salesforce / HubSpot**
2. **Zapier triggers Company Intelligence** → enriched company JSON flows back
3. **Zapier triggers People Intelligence** → enriched contact JSON flows back
4. **Contact created automatically** with title, seniority, likely email, and activity signals

**Cost per contact: $0.10.** No monthly subscription. No seats. No contracts.

Compare to:

- Apollo: ~$1/contact (10x more)
- ZoomInfo: ~$5-15/contact (50-150x more)
- Clay: $400+/month minimum
- Manual research: 15-30 minutes per person

***

### What It Does

Given a person's **name + company** (or LinkedIn URL), output structured intelligence:

| Field | Example |
|---|---|
| Name + title | "Sarah Chen — VP of Marketing" |
| Seniority level | "VP-Director" |
| Department | "Marketing" |
| Team size estimate | "10-30" |
| LinkedIn URL | `linkedin.com/in/sarah-chen-acme` |
| Likely email formats | `sarah.chen@acme.com`, `schen@acme.com` |
| Email format confidence | "high" |
| Recent activity signals | "Job change: joined Acme 8 months ago" |
| Confidence score | 82/100 |

***

### Quick Start

#### Input (single person)

```json
{
  "name": "Sarah Chen",
  "company": "Acme Corp"
}
```

#### Input (with LinkedIn URL for higher confidence)

```json
{
  "name": "Sarah Chen",
  "company": "Acme Corp",
  "linkedinUrl": "https://www.linkedin.com/in/sarah-chen-acme"
}
```

#### Input (batch mode — up to 50 people per run)

```json
{
  "people": [
    { "name": "Sarah Chen", "company": "Acme Corp" },
    { "name": "James Park", "company": "Stripe" },
    { "name": "Maria Santos", "company": "HubSpot" }
  ],
  "depth": "standard"
}
```

***

### Example Output

```json
{
  "name": "Sarah Chen",
  "title": "VP of Marketing",
  "seniority": "VP-Director",
  "company": "Acme Corp",
  "companyDomain": "acme.com",
  "department": "Marketing",
  "teamSizeEstimate": "10-30",
  "linkedinUrl": "https://www.linkedin.com/in/sarah-chen-acme",
  "linkedinHeadline": "VP Marketing @ Acme | B2B SaaS | Pipeline obsessed",
  "location": "San Francisco, CA",
  "likelyEmailFormats": [
    "sarah.chen@acme.com",
    "schen@acme.com",
    "sarah@acme.com",
    "sarachen@acme.com"
  ],
  "emailFormatConfidence": "high",
  "recentActivity": [
    "Posted about demand gen strategy 3 days ago",
    "Job change: joined Acme Corp 8 months ago",
    "Commented on pipeline metrics article"
  ],
  "openToOutreach": true,
  "confidenceScore": 82,
  "confidenceNotes": "LinkedIn profile confirmed. Email format inferred from company domain patterns.",
  "sources": [
    "https://www.linkedin.com/in/sarah-chen-acme",
    "https://acme.com/team"
  ],
  "analyzedAt": "2026-02-28T12:00:00.000Z",
  "error": null
}
```

***

### Input Reference

| Field | Type | Required | Description |
|---|---|---|---|
| `name` | string | Yes\* | Full name of person |
| `company` | string | Yes\* | Company name or domain |
| `linkedinUrl` | string | No | Direct LinkedIn URL (increases confidence) |
| `people` | array | — | Batch mode: array of `{name, company, linkedinUrl?}` |
| `depth` | string | No | `"standard"` (default) or `"quick"` |
| `includeEmailFormat` | boolean | No | Default `true` |

\*Either `name`+`company` or `linkedinUrl` is required.

***

### Pricing

| Result | Price |
|---|---|
| Person analyzed (confidence ≥ 50) | **$0.10** |
| Person not found (confidence < 50) | **$0.00** |
| Batch of 10 people | **~$1.00** |
| Batch of 100 people | **~$10.00** |
| Batch of 1,000 people | **~$100.00** |

**Pay-per-event (PPE)** — you only pay for successful analyses. If we can't find meaningful data on someone, you're not charged.

***

### Confidence Score

| Score | Meaning |
|---|---|
| 85-100 | LinkedIn confirmed + title + company verified |
| 65-84 | LinkedIn found, data partially verified |
| 40-64 | Inferred from company/web signals only |
| < 40 | Very limited data — no charge |

***

### MCP / AI Agent Compatible

This actor is available via the [Apify MCP server](https://mcp.apify.com/), making it natively usable inside:

- **Claude** (claude.ai or Claude Desktop with MCP)
- **Cursor** / **VS Code** (via MCP plugin)
- Any MCP-compatible AI agent or tool

Zero integration work. Call it from your AI assistant in 30 seconds.

***

### Integrations (Zero-Code)

Works out of the box with all Apify native integrations:

| Integration | Use case |
|---|---|
| **Zapier** | Trigger on new CRM lead → enrich → create enriched contact |
| **Make (formerly Integromat)** | Same as Zapier, more complex flows |
| **Google Sheets** | Results populate a sheet automatically |
| **Slack** | Send enriched contact to a Slack channel |
| **HubSpot** | Direct integration available |
| **Salesforce** | Via Zapier or direct API |

**Example Zapier flow (5 minutes to set up):**

```
Trigger: New contact in Salesforce
→ Action 1: Company Intelligence (enrich company)
→ Action 2: People Intelligence (enrich contact)
→ Action 3: Update Salesforce contact with enriched fields
```

***

### API Usage

```bash
curl -X POST "https://api.apify.com/v2/acts/fortunate_favorite~people-intelligence/runs" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -d '{
    "name": "Sarah Chen",
    "company": "Acme Corp"
  }'
```

***

### Companion Actor

Works best paired with **[Company Intelligence](https://apify.com/fortunate_favorite/company-intelligence)** ($0.20/company):

1. Company Intelligence → understand the account (tech stack, size, pain points, opportunity score)
2. People Intelligence → find the right contact (title, seniority, email format, activity)
3. Outreach → go in warm, with context

***

### Always Fresh — Powered by Gemini (Google)

Unlike database-backed tools (Apollo, ZoomInfo, Clay) where contact data can be months or years out of date, every run of this actor fetches live data in real time:

- **LinkedIn public profile** fetched fresh on every run — current title, headline, recent activity
- **Company team page** scraped live — catches recent hires and org changes
- **Google web signals** checked for job changes, posts, and public activity

Google Gemini Flash synthesises all of this into structured contact intelligence — so you get a picture of who this person is *today*, not who they were when a database last crawled them.

**What's AI-inferred vs. sourced** is clearly labelled in the `dataQuality` field of every output. Email formats are labelled `inferredEmailFormats` — pattern-based guesses, not verified addresses. The `confidenceScore` is AI-estimated and reflects data availability, not a guaranteed match.

> Data privacy: inputs are processed by Google's Generative AI API. See [Google's privacy policy](https://policies.google.com/privacy). Supply your own API key via the `googleApiKey` input field for high-volume or sensitive use cases. Free API keys available at [aistudio.google.com/apikey](https://aistudio.google.com/apikey).

**Other notes:**

- LinkedIn data comes from **publicly indexed pages** only — no login, no cookies required.
- Person not found = no charge. We only charge when we deliver meaningful intelligence.
- LinkedIn profiles may have access limits; actor falls back to Google-indexed snippets when needed.

***

### Support

Questions or issues? Contact us via the Apify actor page or open an issue.

Built with ❤️ using Apify + Google Gemini Flash.

# Actor input Schema

## `name` (type: `string`):

Full name of the person to analyze (e.g. 'Sarah Chen')

## `company` (type: `string`):

Company name or domain the person works at (e.g. 'Stripe' or 'stripe.com'). Required unless linkedinUrl is provided.

## `linkedinUrl` (type: `string`):

Direct LinkedIn profile URL if you have it. Speeds up analysis and increases confidence score.

## `people` (type: `array`):

Analyze multiple people at once. Each item: { name, company, linkedinUrl? }

## `depth` (type: `string`):

'quick' = LinkedIn + email format only (fastest). 'standard' = LinkedIn + company team page + web signals (recommended).

## `includeEmailFormat` (type: `boolean`):

Infer likely email formats from company domain patterns. Always recommended for outreach.

## `anthropicApiKey` (type: `string`):

Your own Anthropic API key for high-volume use. If not provided, the actor uses the shared key. Get yours at console.anthropic.com.

## Actor input object example

```json
{
  "name": "Sarah Chen",
  "company": "Stripe",
  "linkedinUrl": "https://www.linkedin.com/in/sarah-chen",
  "people": [
    {
      "name": "Sarah Chen",
      "company": "Acme Corp"
    },
    {
      "name": "James Park",
      "company": "Stripe"
    }
  ],
  "depth": "standard",
  "includeEmailFormat": true
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("fortunate_favorite/people-intelligence").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("fortunate_favorite/people-intelligence").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call fortunate_favorite/people-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,fortunate_favorite/people-intelligence"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/GxSSfIltpTVIUfGa3/builds/mI7CKoXmNIsLfUtBH/openapi.json