Integrations

Supercharge People Data Labs with Relevance AI

People Data Labs is a powerful tool that offers extensive person and company data through an easy-to-use API. With Relevance AI, you can elevate this data to new heights, enabling smarter decision-making and enhanced data-driven strategies.

Give your AI Agents People Data Labs Superpowers

People Data Labs provides access to a vast database of individuals and companies, while Relevance AI empowers you to leverage this data through intelligent AI Agents that can analyze, trigger actions, and scale your insights.

Instant Knowledge Amplification

The agent gains immediate access to over 2.5 billion professional profiles, supercharging its ability to understand and analyze human professional networks.

Network Insight Mastery

Develops deep understanding of professional relationships and organizational structures through advanced company and contact data analysis.

Predictive Understanding

Utilizes historical and current professional data to anticipate needs and provide proactive recommendations.

Tools

Equip AI Agents with the People Data Labs Tools they need

Relevance AI seamlessly integrates with People Data Labs to enhance your workflows with enriched person and company data.

People Data Labs - Enrich a Person
Enriches person profiles by retrieving comprehensive data about individuals using various identifiers like name, email, location, and social profiles
People Data Labs - Search People
Enables advanced searching of people records using either Elasticsearch or SQL queries with customizable result parameters and dataset filtering
Raw People Search
Performs direct people searches using raw Elasticsearch queries with configurable result limits and detailed output including execution metrics
People Data Labs - Enrich a Company
Retrieves detailed company information and enriches existing company profiles using various identifiers including name, location, and social presence
Name
People Data Labs API Call
Description
Make an authorized request to a People Data Labs API
Parameters
["OAuth account authentication", "Multiple HTTP methods (GET, POST, PUT, DELETE, PATCH)", "Custom headers support", "Configurable request body", "Relative path customization"]
Use Case
A recruiting firm uses People Data Labs API to enrich their candidate database by automatically fetching professional history and contact details for prospects, enabling more targeted outreach and improved candidate matching.

Security & Reliability

The integration between People Data Labs (PDL) and Relevance AI leverages secure OAuth authentication, ensuring that only authorized workflows can access your extensive person and company data. Relevance AI manages API operations (such as enriching profiles and performing searches) seamlessly in the background, allowing you to focus on deriving insights without worrying about errors, formatting, or rate limits.

With built-in validation and type conversion, your workflows will operate smoothly, even when dealing with varying data formats. This integration empowers you to enrich profiles with detailed demographic and professional data, perform advanced searches using Elasticsearch or SQL queries, and access standardized data across multiple datasets.

No training on your data

Your data remains private and is never utilized for model training purposes.

Security first

We never store anything we don’t need to. The inputs or outputs of your tools are never stored.

Get Started

Best Practices for Non-Technical Users

To get the most out of the People Data Labs + Relevance AI integration without writing code:
  • Provide comprehensive input data: Always include multiple identifying fields such as name, email, and company for better enrichment results.
  • Utilize batch requests: When enriching or searching for multiple profiles, batch your requests to improve performance and reduce API calls.
  • Implement caching: Store frequently accessed data locally to minimize redundant API calls and enhance response times.
  • Monitor API usage: Keep an eye on your rate limits and implement throttling to avoid hitting the maximum request threshold.
  • Handle errors gracefully: Implement robust error handling to manage authentication issues, rate limits, and data quality problems effectively.