DataVertex vs. People Data Labs: Which Recruitment Enrichment API Is Better for Recruiting Products?

If you're building a recruiting product today, chances are you've evaluated both DataVertex and People Data Labs (PDL).

Both platforms provide large-scale people datasets through APIs. Both can power candidate search, enrichment, and recruiting workflows. But they were built with different goals in mind.

Rather than declaring one platform "better," this guide compares where each solution fits best so you can decide which aligns with your product roadmap.

At a Glance

Category	DataVertex	People Data Labs
Primary focus	Recruiting technology	Multi-industry people & company data
People dataset	800M+ candidate profiles	Large global people dataset plus company data
Company dataset	Not currently available	60M+ companies
Natural language search	✅ Yes	No (structured queries)
Semantic search	✅ Yes	No
Job description search	✅ Yes	No
Candidate contact data	Extensive validated personal email & mobile coverage	Available, but generally lighter coverage and validation rate
API Pricing model	Browse up to 100 candidates for one search credit	Charged per returned record
Delivery	API	API + Data License
Best suited for	ATS, AI Recruiters, CRM, Sourcing Tools, Staffing Agencies	Analytics, GTM, Sales, Investment Intelligence, Recruiting

Different Philosophies

Although both companies expose people data through APIs, they were designed for different use cases.

People Data Labs is a general-purpose people data platform. Its customers span sales technology, marketing technology, fraud detection, investment intelligence, HR technology, and analytics. It offers APIs alongside bulk data licensing and company datasets.

DataVertex is purpose-built for recruiting products. Every API endpoint is designed around recruiter workflows, sourcing experiences, ATS integrations, CRM enrichment, and AI recruiting agents.

This difference influences nearly every aspect of each platform.

How Industry Experience Shapes the Product

The backgrounds of a company's founders and product team often influence how a platform evolves.

People Data Labs

People Data Labs has built its platform around collecting, organizing, and delivering large-scale people and company data for a wide range of industries. Its products support use cases spanning sales intelligence, marketing, investment research, fraud detection, workforce analytics, and recruiting. This broad customer base has led to a highly flexible data platform that can be adapted to many applications.

DataVertex

DataVertex was founded by a team with years of experience building products for the HR technology industry. Before starting DataVertex, the founders worked with and alongside dozens of recruiting platforms, sourcing tools, applicant tracking systems (ATS), recruiting CRMs, and talent intelligence startups.

That experience shaped the product from day one. Instead of starting with a general people database and adapting it for recruiting, DataVertex was designed around how recruiters actually search for candidates, review results, enrich contact information, and integrate these workflows into recruiting products.

For engineering teams building recruiting software, this recruiting-first perspective often translates into APIs, search capabilities, and workflows that require less customization to fit recruiter expectations.

Search Experience

One of the biggest differences is how users search.

People Data Labs

PDL's Search API is extremely flexible but primarily expects structured SQL or Elasticsearch-style queries against hundreds of available fields. This provides significant power for technical users building custom search logic.

Examples include:

• title = "Software Engineer"

• location = "London"

• company = "Google"

For engineering teams building sophisticated data products, this flexibility can be valuable.

DataVertex

DataVertex focuses on helping recruiters find the right candidates faster.

Apart from supporting structured search queries, it also supports:

• Natural language search

• Semantic search

• Job description search

• AI-friendly search experiences

For example, users can search with prompts such as:

"Senior backend engineer with Kubernetes experience in New York who has worked in Fintech industry."

This makes it particularly well suited for AI copilots and conversational recruiting products.

Credit Consumption

Pricing models can significantly impact product design.

People Data Labs

PDL generally charges per returned person record.

If a search returns 50 candidate records, each returned record consumes credits. Their documentation also notes that repeated enrichment requests for the same profile incur additional charges unless customers implement their own duplicate detection.

DataVertex

DataVertex separates searching from enrichment.

A single search credit lets users browse up to 100 matching candidates before deciding which candidates they actually want to enrich.

For recruiting workflows where recruiters often review dozens of profiles before selecting a few, this model can be substantially more efficient.

Recruiting Workflow vs General Data Platform

People Data Labs serves many industries.

Examples include:

• Sales intelligence

• Marketing

• Investment intelligence

• Fraud detection

• Workforce analytics

• Recruiting

That breadth makes PDL attractive if your application needs both people and company intelligence.

DataVertex deliberately focuses on one market: Recruiting technology.

That specialization shows up in features like:

• Candidate search

• Candidate enrichment

• Recruiter-friendly search

• ATS workflows

• AI recruiter integrations

• CRM recruiting workflows

  
  

If recruiting is your primary product, using an API designed specifically for recruiter behavior often reduces product complexity.

An example sourcing interface for a recruiting product

Company Data

This is one area where People Data Labs clearly has broader coverage.

People Data Labs

Offers:

• Company search

• Company enrichment

• Company datasets

• Bulk company licensing

This is valuable for:

• Sales platforms

• GTM intelligence

• Market research

• Investment research

DataVertex

Currently focuses exclusively on candidate data.

If your product also requires company intelligence, PDL may support that.

Contact Information for Recruitment Enrichment API

Both platforms include contact information, but they emphasize different priorities.

People Data Labs includes personal emails and phone numbers where available across its global dataset. Customers of People Data Labs may stitch it with other contact providers for contact enrichment use cases.

DataVertex places a stronger emphasis on recruiting-ready, high-quality contact information, with extensive personal email and mobile phone coverage from a robust built-in waterfall enrichment, along with a high email validation rate to support candidate outreach.

For outbound recruiting products, contact coverage can have a meaningful impact on recruiter productivity.

API Integration Experience

Both companies provide REST APIs, SDKs, and developer documentation.

The difference is less about the technology and more about the workflow each API is designed to support.

People Data Labs exposes a broad platform intended to support many different industries and use cases. That flexibility gives developers significant control but may require more application-specific logic when building recruiting experiences.

DataVertex's APIs are organized specifically around recruiting workflows, making it easier to implement features like candidate sourcing, recruiter search experiences, candidate matching, talent rediscovery, ATS database refreshment, and AI recruiting assistants with less custom translation between the API and the product experience.

AI Recruiting Products

The rise of AI recruiting agents is changing how recruiting products search for talent.

Traditional search APIs often assume users will construct filters manually.

Modern AI assistants instead generate searches directly from natural language and job descriptions.

This is where DataVertex's recruiting-specific search capabilities can simplify implementation, particularly for:

• AI sourcing agents

• Conversational recruiters

• Recruiting copilots

• ATS platforms

• Recruiting CRMs

• Staffing Agencies building internal products or workflows

  
  

When People Data Labs May Be the Better Choice

PDL may be a stronger fit if you need:

• People and company data together

• Sales or GTM intelligence

• Investment research

• Bulk data licensing

• Workforce analytics

• No extensive contact information enrichment

When DataVertex May Be the Better Choice

DataVertex may be the stronger choice if you're building:

• Applicant Tracking Systems (ATS)

• AI Recruiters

• Recruiting CRMs

• Candidate sourcing platforms

• Recruiting automation software

• Candidate matching products

• Talent intelligence platforms

Especially if you value:

• Natural language/Semantic search

• Job description search

• Candidate matching

• Recruiting-first APIs

• Higher contact information coverage

• Credit-efficient candidate discovery

Final Thoughts

People Data Labs and DataVertex are both excellent APIs, but they optimize for different outcomes.

People Data Labs is a broad people data platform serving multiple industries with extensive datasets, company intelligence, and flexible search capabilities.

DataVertex is purpose-built for recruiting software. Its APIs are designed around how recruiters actually discover, evaluate, and engage candidates, making it particularly well-suited for ATS platforms, AI recruiting agents, sourcing tools, staffing companies, and recruiting CRMs.

Ultimately, the right choice depends on the product you're building.

If your platform is centered around recruiting workflows, recruiter productivity, and AI-powered talent discovery, a recruiting-focused API can often provide a simpler implementation and a better end-user experience.