Pricing

from $150.00 / 1,000 person enricheds

Person Data Enrichment — Email, Phone & LinkedIn

Enriches persons from People Data Labs — cheaper than Clay, Apollo, or ZoomInfo. Name + company → verified work email, job title, seniority, phone, LinkedIn, and location. Pay-per-event: $0.15/person. No subscription.

Pricing

from $150.00 / 1,000 person enricheds

Rating

0.0

(0)

Developer

Ryan Clinton

Actor stats

Bookmarked

355

Total users

122

Monthly active users

23 days ago

Last modified

Categories

Lead generation

You can access the Person Data Enrichment — Email, Phone & LinkedIn programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

{
  "openapi": "3.0.1",
  "info": {
    "version": "1.4",
    "x-build-id": "CVYVp6h4URNTyvJOo"
  },
  "servers": [
    {
      "url": "https://api.apify.com/v2"
    }
  ],
  "paths": {
    "/acts/ryanclinton~person-enrichment-lookup/run-sync-get-dataset-items": {
      "post": {
        "operationId": "run-sync-get-dataset-items-ryanclinton-person-enrichment-lookup",
        "x-openai-isConsequential": false,
        "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
        "tags": [
          "Run Actor"
        ],
        "requestBody": {
          "required": true,
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/inputSchema"
              }
            }
          }
        },
        "parameters": [
          {
            "name": "token",
            "in": "query",
            "required": true,
            "schema": {
              "type": "string"
            },
            "description": "Enter your Apify token here"
          }
        ],
        "responses": {
          "200": {
            "description": "OK"
          }
        }
      }
    },
    "/acts/ryanclinton~person-enrichment-lookup/runs": {
      "post": {
        "operationId": "runs-sync-ryanclinton-person-enrichment-lookup",
        "x-openai-isConsequential": false,
        "summary": "Executes an Actor and returns information about the initiated run in response.",
        "tags": [
          "Run Actor"
        ],
        "requestBody": {
          "required": true,
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/inputSchema"
              }
            }
          }
        },
        "parameters": [
          {
            "name": "token",
            "in": "query",
            "required": true,
            "schema": {
              "type": "string"
            },
            "description": "Enter your Apify token here"
          }
        ],
        "responses": {
          "200": {
            "description": "OK",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/runsResponseSchema"
                }
              }
            }
          }
        }
      }
    },
    "/acts/ryanclinton~person-enrichment-lookup/run-sync": {
      "post": {
        "operationId": "run-sync-ryanclinton-person-enrichment-lookup",
        "x-openai-isConsequential": false,
        "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
        "tags": [
          "Run Actor"
        ],
        "requestBody": {
          "required": true,
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/inputSchema"
              }
            }
          }
        },
        "parameters": [
          {
            "name": "token",
            "in": "query",
            "required": true,
            "schema": {
              "type": "string"
            },
            "description": "Enter your Apify token here"
          }
        ],
        "responses": {
          "200": {
            "description": "OK"
          }
        }
      }
    }
  },
  "components": {
    "schemas": {
      "inputSchema": {
        "type": "object",
        "required": [
          "persons"
        ],
        "properties": {
          "persons": {
            "title": "Persons to enrich",
            "type": "array",
            "description": "List of persons to enrich. Each entry needs at minimum: name + company/domain, OR email. Supported fields: name, email, company, domain, linkedinUrl.",
            "default": [
              {
                "name": "Jan Curn",
                "company": "Apify",
                "domain": "apify.com"
              }
            ]
          },
          "pdlApiKey": {
            "title": "PDL API Key (optional)",
            "type": "string",
            "description": "Your People Data Labs API key. If left blank, the built-in shared key is used (limited monthly cap across all users). Bring your own for unlimited volume — sign up free at peopledatalabs.com."
          },
          "maxPersons": {
            "title": "Max persons",
            "minimum": 1,
            "maximum": 1000,
            "type": "integer",
            "description": "Maximum number of persons to process. Hard cap to prevent accidental over-billing.",
            "default": 100
          },
          "includeWorkHistory": {
            "title": "Include work history",
            "type": "boolean",
            "description": "Include the person's past job history in the output. Adds detail but increases response payload size.",
            "default": false
          },
          "includeEducation": {
            "title": "Include education",
            "type": "boolean",
            "description": "Include the person's education history (university, degree, field of study) in the output.",
            "default": false
          },
          "includeSkills": {
            "title": "Include skills",
            "type": "boolean",
            "description": "Include the person's listed skills in the output.",
            "default": false
          },
          "validateEmails": {
            "title": "Validate returned emails (MX + disposable + role-account check)",
            "type": "boolean",
            "description": "For every email PDL returns, check that the domain has MX records, flag disposable / temp-mail providers, and flag generic role accounts (info@, sales@). Adds ~1-2 seconds per unique domain. Powers the composite confidenceScore.",
            "default": false
          },
          "useCompanyAliases": {
            "title": "Retry with known company aliases on miss",
            "type": "boolean",
            "description": "When PDL Search returns nothing, retry with known aliases (e.g. Facebook → Meta Platforms, X → Twitter, Alphabet → Google). Catches records that lag behind rebrands. Each alias attempt is one extra PDL call.",
            "default": true
          },
          "compareToPrevRun": {
            "title": "Detect changes since last run (job changes, promotions, email changes)",
            "type": "boolean",
            "description": "Snapshot every enriched person to a named KV store, then on the next run diff against the prior snapshot. Adds changeFlags[] (NEW_PERSON, JOB_CHANGED, PROMOTION, TITLE_CHANGED, EMAIL_CHANGED, LOCATION_CHANGED, etc.) and a changeSinceLastRun block to every record. Schedule weekly to catch job changes while they are still timely.",
            "default": false
          },
          "monitorStateKey": {
            "title": "Monitor state KV store name (advanced)",
            "type": "string",
            "description": "Override the named KV store used for cross-run snapshots. Defaults to 'person-enrichment-monitor'. Use a different name to keep separate snapshot histories per CRM segment / campaign."
          },
          "changeFlagsFilter": {
            "title": "Restrict output to these change flags (only when compareToPrevRun is on)",
            "type": "array",
            "description": "Only save records that match at least one of these change flags. Example: ['JOB_CHANGED', 'PROMOTION'] for re-engagement campaigns. Leave empty to save all records. Filtered records are not charged.",
            "items": {
              "type": "string"
            }
          },
          "minConfidenceScore": {
            "title": "Minimum confidence score (0–100)",
            "minimum": 0,
            "maximum": 100,
            "type": "integer",
            "description": "Only save records scoring at or above this composite confidence. Lower-scoring records are skipped (and not charged). Leave blank to use the matchStrategy default (strict=75, balanced=none, aggressive=none). Recommended floor for cold outreach: 50."
          },
          "matchStrategy": {
            "title": "Match strategy",
            "enum": [
              "strict",
              "balanced",
              "aggressive"
            ],
            "type": "string",
            "description": "Strict = high-confidence only (PDL likelihood >=6, default minConfidenceScore=75). Balanced (default) = full fallback chain, no auto-floor. Aggressive = broadest search (likelihood >=1, top-5 candidates, accepts lower-confidence matches when company domain aligns).",
            "default": "balanced"
          },
          "requireFields": {
            "title": "Required output fields",
            "type": "array",
            "description": "Skip + don't charge records missing any of these fields. Filter runs AFTER enrichment + validation, BEFORE pushData + charge. Allowed values: email, personalEmail, phone, mobilePhone, linkedinUrl, jobTitle, companyName, companyDomain.",
            "items": {
              "type": "string"
            }
          },
          "dedupeMode": {
            "title": "Input deduplication mode",
            "enum": [
              "off",
              "strict",
              "fuzzy"
            ],
            "type": "string",
            "description": "Off = enrich every input row. Strict = collapse exact (lowercased) name + email + linkedin matches. Fuzzy = also collapses whitespace, punctuation, and company-name suffixes (Inc/Corp/Ltd) so 'Acme' + acme.com == 'Acme Corp' + acme.com.",
            "default": "off"
          },
          "skipPreviouslyEnriched": {
            "title": "Skip recently-enriched persons",
            "type": "boolean",
            "description": "When the monitor KV store contains a fresh snapshot for a person (within freshnessWindowDays), echo the cached values and skip the PDL call. Massive cost saver on weekly schedules. Requires a populated monitor state — first run on a new state key always hits PDL.",
            "default": false
          },
          "freshnessWindowDays": {
            "title": "Freshness window (days)",
            "minimum": 1,
            "maximum": 365,
            "type": "integer",
            "description": "How many days a snapshot stays 'fresh' enough to skip on rerun (only used when skipPreviouslyEnriched is on). Default 30. Lower = more re-enrichment, higher = more cost savings but staler data.",
            "default": 30
          },
          "includeCandidates": {
            "title": "Include alternate match candidates",
            "type": "boolean",
            "description": "Fetch up to 5 candidates per person from PDL Search and surface alternates under matchDebug.alternates[]. Alternates are NOT charged, NOT separate dataset rows, NOT enriched further — they exist purely so you can audit the winning match.",
            "default": false
          },
          "includeMatchDebug": {
            "title": "Include match transparency block",
            "type": "boolean",
            "description": "Attach a matchDebug block to every record with strategyPreset, inputSignalsUsed, candidatesConsidered, and selectedReason. Auto-enabled when includeCandidates is on. Useful for trust-building and debugging bad matches.",
            "default": false
          }
        }
      },
      "runsResponseSchema": {
        "type": "object",
        "properties": {
          "data": {
            "type": "object",
            "properties": {
              "id": {
                "type": "string"
              },
              "actId": {
                "type": "string"
              },
              "userId": {
                "type": "string"
              },
              "startedAt": {
                "type": "string",
                "format": "date-time",
                "example": "2025-01-08T00:00:00.000Z"
              },
              "finishedAt": {
                "type": "string",
                "format": "date-time",
                "example": "2025-01-08T00:00:00.000Z"
              },
              "status": {
                "type": "string",
                "example": "READY"
              },
              "meta": {
                "type": "object",
                "properties": {
                  "origin": {
                    "type": "string",
                    "example": "API"
                  },
                  "userAgent": {
                    "type": "string"
                  }
                }
              },
              "stats": {
                "type": "object",
                "properties": {
                  "inputBodyLen": {
                    "type": "integer",
                    "example": 2000
                  },
                  "rebootCount": {
                    "type": "integer",
                    "example": 0
                  },
                  "restartCount": {
                    "type": "integer",
                    "example": 0
                  },
                  "resurrectCount": {
                    "type": "integer",
                    "example": 0
                  },
                  "computeUnits": {
                    "type": "integer",
                    "example": 0
                  }
                }
              },
              "options": {
                "type": "object",
                "properties": {
                  "build": {
                    "type": "string",
                    "example": "latest"
                  },
                  "timeoutSecs": {
                    "type": "integer",
                    "example": 300
                  },
                  "memoryMbytes": {
                    "type": "integer",
                    "example": 1024
                  },
                  "diskMbytes": {
                    "type": "integer",
                    "example": 2048
                  }
                }
              },
              "buildId": {
                "type": "string"
              },
              "defaultKeyValueStoreId": {
                "type": "string"
              },
              "defaultDatasetId": {
                "type": "string"
              },
              "defaultRequestQueueId": {
                "type": "string"
              },
              "buildNumber": {
                "type": "string",
                "example": "1.0.0"
              },
              "containerUrl": {
                "type": "string"
              },
              "usage": {
                "type": "object",
                "properties": {
                  "ACTOR_COMPUTE_UNITS": {
                    "type": "integer",
                    "example": 0
                  },
                  "DATASET_READS": {
                    "type": "integer",
                    "example": 0
                  },
                  "DATASET_WRITES": {
                    "type": "integer",
                    "example": 0
                  },
                  "KEY_VALUE_STORE_READS": {
                    "type": "integer",
                    "example": 0
                  },
                  "KEY_VALUE_STORE_WRITES": {
                    "type": "integer",
                    "example": 1
                  },
                  "KEY_VALUE_STORE_LISTS": {
                    "type": "integer",
                    "example": 0
                  },
                  "REQUEST_QUEUE_READS": {
                    "type": "integer",
                    "example": 0
                  },
                  "REQUEST_QUEUE_WRITES": {
                    "type": "integer",
                    "example": 0
                  },
                  "DATA_TRANSFER_INTERNAL_GBYTES": {
                    "type": "integer",
                    "example": 0
                  },
                  "DATA_TRANSFER_EXTERNAL_GBYTES": {
                    "type": "integer",
                    "example": 0
                  },
                  "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                    "type": "integer",
                    "example": 0
                  },
                  "PROXY_SERPS": {
                    "type": "integer",
                    "example": 0
                  }
                }
              },
              "usageTotalUsd": {
                "type": "number",
                "example": 0.00005
              },
              "usageUsd": {
                "type": "object",
                "properties": {
                  "ACTOR_COMPUTE_UNITS": {
                    "type": "integer",
                    "example": 0
                  },
                  "DATASET_READS": {
                    "type": "integer",
                    "example": 0
                  },
                  "DATASET_WRITES": {
                    "type": "integer",
                    "example": 0
                  },
                  "KEY_VALUE_STORE_READS": {
                    "type": "integer",
                    "example": 0
                  },
                  "KEY_VALUE_STORE_WRITES": {
                    "type": "number",
                    "example": 0.00005
                  },
                  "KEY_VALUE_STORE_LISTS": {
                    "type": "integer",
                    "example": 0
                  },
                  "REQUEST_QUEUE_READS": {
                    "type": "integer",
                    "example": 0
                  },
                  "REQUEST_QUEUE_WRITES": {
                    "type": "integer",
                    "example": 0
                  },
                  "DATA_TRANSFER_INTERNAL_GBYTES": {
                    "type": "integer",
                    "example": 0
                  },
                  "DATA_TRANSFER_EXTERNAL_GBYTES": {
                    "type": "integer",
                    "example": 0
                  },
                  "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                    "type": "integer",
                    "example": 0
                  },
                  "PROXY_SERPS": {
                    "type": "integer",
                    "example": 0
                  }
                }
              }
            }
          }
        }
      }
    }
  }
}

B2B Person Enrichment API — Email, Title, Lead Scoring OpenAPI definition

OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.

OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.

By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.

You can download the OpenAPI definitions for Person Data Enrichment — Email, Phone & LinkedIn from the options below:

OpenAPI.json

If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.

You can also check out our other API clients:

Person Data Enrichment — Email, Phone & LinkedIn API in Python

Person Data Enrichment — Email, Phone & LinkedIn API in JavaScript

Person Data Enrichment — Email, Phone & LinkedIn API through CLI

Person Data Enrichment — Email, Phone & LinkedIn API

Email Enrichment

tomba-io/email-enrichment

Enrichment lets you find the current job title, company,location and social profiles of the person behind the email. 💡

Tomba io

116

Dentist Finder

cleansyntax/dentist-finder

Dentist Finder is a comprehensive database providing access to detailed information on all licensed dentists across the USA. This API delivers up-to-date data, including contact details, specialties, office locations, and more.

Sam

158

4.0

🚀 Leads Finder similar to Apollo Zoominfo Linkedin

peakydev/leads-finder-apollo-linkedin

🚀 Extract verified leads from a single search URL of your b2b platform with emails, phone numbers, and company details similar to Apollo, LinkedIn, Zoominfo

Peaky Dev

5.0

Company Data Enrichment for Pennies

naive_zing/skraper

Wyald

145

Dentist & Doctor Lead Scraper — Verified Emails

samstorm/dentist-lead-scraper

Scrape dentist, doctor & clinic contacts from Google Maps with verified emails, phones & social links. Real-time data, not stale databases. Export to HubSpot, Salesforce, or CSV. Perfect for healthcare marketing, dental SaaS sales & medical recruiting.

Sam Kleespies

254

VK People Scraper 🔍 (вконтакте)

scrapestorm/vk-people-scraper-vkontakte

Scrape VK profiles based on a specific keyword 🔑 to discover targeted users. Filter by gender 👩 & retrieve valuable data like profile names 🧑‍🤝‍🧑 location 🌍 and education 🎓. Boost your marketing research with VK data🚀 Perfect for analyzing VK аудитория. Извлечение профилей по ключевому слову

Storm_Scraper

5.0

VK Video Scraper 🎬 (вконтакте)

scrapestorm/vk-video-scraper-vkontakte

Scrape VK videos based on keywords 🎥🔑 and max items to fetch videos. Filter by keyword, and collect data like video title 📹, description, views 👀, likes ❤️, reposts 🔄, and more. Enhance your video marketing research 🚀. Perfect for analyzing video VK аудитория через видео.

Storm_Scraper

5.0

LinkedIn Contact Enricher

lead_king/linkedin-contact-enricher

Turn LinkedIn profile URLs into verified emails and phone numbers. Bulk enrichment, CSV/JSON export, CRM-ready. Pay only for contacts found — no API key.

Lead King

VK Scraper (All-in-one) 👥🌐🎬

scrapestorm/vk-scraper-all-in-one

Scrape VK (вконтакте) profiles, communities, & videos (All-in-one) in a single scraper based on a specific keyword 🔑 and a maximum number of items. Filter by scraper type and retrieve key data such as names, links 🌍, & descriptions 🎓. Enhance your marketing research by analyzing VK audience data

Storm_Scraper

5.0

NPPES NPI Healthcare Provider Crawler

jungle_synthesizer/nppes-npi-crawler

Crawl healthcare provider records from the CMS NPPES NPI Registry. Extract NPI numbers, names, credentials, specialties, taxonomy codes, practice addresses, and phone numbers. Filter by state, specialty, city, ZIP, and provider type. Ideal for pharma sales, medical devices, and provider directories.