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Engineering Teams- Enrichment and Standardization API

People Data Labs is a data company

 

We build people data - that's it. We are a deeply technical company that only does one thing.


Our Mission

All enterprises will become people data companies over the next decade. It will be crucial for enterprises to generate insights, build analytics, make predictions, recommend products, build comprehensive customer analysis, fight fraud, and hundreds of other use cases with the data on people they collect.

We're committed to working with engineering, data, product, and other technical customers to help them achieve their people data based innovation goals.

 

What we do

We are your data partner who is focused on people data. We work with our customers in a deeply technical manner to provide them the most accurate people data on the market, as well as technology to create a standard people data format internally. 

We partner with our customers on people data building related challenges as they focus on innovating on top of our data. For enterprises, we combine a mixture of our products, data, and our engineering team working alongside your data infrastructure, data building, security, and data science teams to achieve your people data goals.

 

 

AN Engineering Culture

We are a deeply technical, engineering focused company. The majority of our team are engineers, and this won't change.

 

 

Our core values 

1. 100% committed to building people data - nothing else.

2. We are a first principles, engineering focused company.

3. We work with engineering, data, data science, product, and other technical customers.

4. We believe in companies using data for good.

  

Company Offices

Headquarters: 455 Market Street Suite 1670, San Francisco, CA 94105

Engineering office: 519 SW 3rd Street 8th Floor, Portland, OR 97204

  

 

BACKED BY Engineers

We are backed by two leading data science venture capital firms who share our vision to build a world class engineering company. 

   8VC InvestorSusa Ventures Investor