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Coresignal is a public web data provider of AI-enriched multi-source data on companies, employees, and jobs. It serves over 1000 leading companies creating products in AI development, investment, sales technology, HR technology, and market research.

2016

founding year

1000+

clients

80+

employees

EWDCI

EWDCI certified

Ethical web data collection initiative

Datarade top data provider 2025

Top data provider

Datarade • 2024-2026

Crozdesk trusted vendor badge 2025

Trusted vendor

Crozdesk • 2025

Crozdesk quality choice badge 2025

Quality choice

Crozdesk • 2025

We were mentioned in:

Media coverage

data-driven industry benchmarking

What Makes Data AI-ready? 3 Must-Have Features for 2026

January 14, 2026

data-driven industry benchmarking

DataDrivenInvestor

Why Integrated Multi-Source Data Is the Future of AI-Powered Entrepreneurship

December 16, 2025

data-driven industry benchmarking

Coresignal Partners With NYU Researchers to Study the Impact of Affirmative Action Ruling on U.S. Hiring Practices

October 16, 2025

data-driven industry benchmarking

Coresignal and the School of Economics at the University of Edinburgh Will Partner to Study Gendered Wording in the Job Ads

September 23, 2025

data-driven industry benchmarking

The 10 best states to look for a remote job in right now, according to new research

data-driven industry benchmarking

Fewer workers want to be in office full-time than ever, but bosses are winning the back-to-work battle

Company news

10 Years of Coresignal: From Web Data Provider to AI-Native Infrastructure

What started as a small startup with a mission to make professional web data accessible to everyone has grown into a global platform we're genuinely proud of. Today, we are a team of over 80 people, trusted by more than 1,000 companies, with datasets covering 4.5 billion companies, professionals, and jobs worldwide.

Karolis Didziulis

Multi-Source Employee Dataset is Now Delivered Daily

The Multi-Source Employee Dataset is now delivered daily. Get fresh workforce data for outreach, sourcing, and AI matching.

Laurynas Gruzinskas

Introducing the B2B Company Posts Dataset

Explore Coresignal’s Company Posts Dataset, featuring structured public company content for market research, trend analysis, AI applications, lead generation, and competitive intelligence.

Pro bono program

Accelerating scientific research

Coresignal's pro bono program provides free data access to researchers from world's leading universities

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Get in touch

For media inquiries or to contact our data experts, please reach out to us at [email protected]

Karolis Didziulis

Product Director

Areas of expertise:

Data business strategy

Data-driven decision making

Web data use cases

Author’s publications:

Why Integrated Multi-Source Data Is the Future of AI-Powered Entrepreneurship

December 16, 2025

Redefining Ethical Web Scraping in the Wake of the Generative AI Boom

December 19, 2024

How Can You Attract and Retain Top Tech Talent?

October 14, 2024

Go Clean to Be Lean: Data Optimization for Improved Business Efficiency

Go Clean to Be Lean: Data Optimization for Improved Business Efficiency

How to Build an Efficient Data Team to Work with Public Web Data

September 23, 2023

Clean Data, Clear Insights: How Web Data Cleaning Elevates Decision-Making

January 30, 2024

Navigating the Future: AI, ML, and the New Era of Public Web Data

January 19, 2024

Things You Should Know When Scaling Your Web Data-Driven Product

August 25, 2023

Database APIs vs Datasets: Weighing Benefits, Drawbacks, and Transition Strategies

Database APIs: Benefits, Limitations, and When You Should Switch to Datasets

Database APIs: Benefits, Limitations, and When You Should Switch to Datasets

Laurynas Gruzinskas

Laurynas Gruzinskas

Head of Product

Areas of expertise:

Data products

Web data for startups

Web data use cases for AI

Author’s publications:

What Makes Data AI-ready? 3 Must-Have Features for 2026

January 14, 2026

Ace in the Hole: Job Listing Data for Your Sales Strategy

Data Engineers, Here’s How LLMs Can Make Your Lives Easier

Harnessing the Potential of Web Data in Investment With Advanced AI Techniques

February 26, 2024

The Best, the Worst, and the Unusual: Ways to Leverage Company & Employee Data

5 Unusual Ways Businesses Use Data from Public Job Postings

January 8, 2024

How to Streamline Web Data Processing With AI in 2024

February 9, 2024

Untraditional Ways To Discover Tech Talent And Promising Software Projects

October 25, 2023

When Should Your Startup Consider Using Public Web Data?

October 16, 2023

Lukas Racickas

Principal Product Manager

Areas of expertise:

Data quality and management

Data APIs

Public web data

Author’s publications:

The critical role of data cleaning

How Public Web Data Can Improve Your Sales Intelligence

Data Blending: Manage Your Data Efficiently and Cost-Effectively

September 1, 2023

The Crucial Role of Data Lifecycle Management in Driving Business Success

September 1, 2023

Data Transformation 101: Process and New Technologies

Data transformation 101: Process and new technologies

How to Build or Transform Recruitment Platforms Using Web Data?

Processes and New Technologies in Data Transformation

How to Build or Transform Recruitment Platforms Using Web Data?

Using web data to transform recruitment platforms

How Public Web Data Can Improve Your Sales Intelligence

From Raw Data to Actionable Insights: The Power of Data Aggregation

From Raw Data to Actionable Insights: The Power of Data Aggregation

The Benefits And Core Processes of Data Wrangling

The Benefits And Core Processes of Data Wrangling

How to Improve VC Deal Sourcing Using Public Web Data

Public Web Data Guide for VC Deal Sourcing

What Are the Key Differences Between Qualitative and Quantitative Data?

February 16, 2023

How to Use Public Web Data for Talent Intelligence and Sourcing?

February 21, 2023

What Are the Key Differences Between Qualitative and Quantitative Data?

February 16, 2023

How to Use Public Web Data for Talent Intelligence and Sourcing?

February 12, 2023

Data Quality: Its Definitions And How to Improve It

February 3, 2023

What Are the Key Differences Between Structured and Unstructured Data?

February 2, 2023

Understanding the Main Differences between Structured and Unstructured Data

January 31, 2023

Data Quality, Its Definitions, And How to Improve It

January 24, 2023

Public Web Data for Business: Common Challenges And How to Solve Them

January 11, 2023

Public Web Data for Business: Common Challenges And How to Solve Them

January 9, 2023

How to Achieve Optimal Business Results with Public Web Data

December 4, 2022

How to Get Started With Public Web Data

December 14, 2022

Jurgita Motus

Senior Data Analyst

Areas of expertise:

Data processing and analysis using open-source tools

Predictive models

Author’s publications:

Automating Data Quality Checks: A Practical Guide Using Dagster and Great Expectations

September 23, 2025

The Rise of Open-Source Data Catalogs: New Opportunities For Implementing Data Mesh

September 23, 2025

Dagster + Great Expectations: The Open Source Duo Transforming Data Quality Pipelines

Open-Source Data Catalogs: A New Chance to Implement Data Mesh

Traditional Monitoring Is Dead. Long Live Data Observability

The Rise of Open-Source Data Catalogs: A New Opportunity For Implementing Data Mesh

November 19, 2024

Automating Data Quality Checks with Dagster and Great Expectations

October 7, 2024

Building a Robust Data Observability Framework to Ensure Data Quality and Integrity

August 27, 2024

Ugnius Zasimauskas

Head of Data Strategy & Sales

Areas of expertise:

AI-ready data

Data strategy

Sales prospecting

Author’s publications:

How to Use Big Data to Gain a Competitive Advantage in Your Industry?

October 19, 2024