Professional network data

Leverage our top B2B datasets

Job posting data

Get access to hundreds of millions of jobs

Employee review data

Get data for employee sentiment analysis

Clean dataNEW

Enhanced professional network data

Employee data

Get data on global talent at scale

Funding data

Discover and analyze funding deals

Firmographic data

Unlock a 360° view of millions of companies

Technographic data

Analyze companies’ tech stacks

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clean data

Reduce time to value with clean data

  • Spend less data engineering resources
  • Leverage 20+ additional data points for more precise analysis
  • Access 494M+ clean company and employee data records
  • Get flat files or use a highly scalable API


data structure


data fields




digestible datasets


delivery and formats

What is clean data?

Data points Example values
company_name Benur Mobility
company_location_hq_country France
company_industry Automotive
company_size_range 501-1000 employees
company_description “Making the best EVs in the world”
company_specialties Outplacements & Trainings

What is clean data?

Clean data refers to professional network data that was processed by removing outliers, unifying values, and eliminating irrelevant or low-value records. For example, stylistic code tags, present in raw data, are removed.

After cleaning, these datasets are also enriched with additional data. Our clean datasets are refined and enhanced versions of our raw datasets. It is the go-to solution for companies that have limited data engineering capabilities or want to reduce their time to value.

Ready-to-use clean datasets

Filtered, unified, and standardized clean datasets. Enriched by leveraging a carefully instructed large language model (LLM).

Company data

Our clean dataset consists of over 35 million high-value B2B company records. Duplicate and incomplete profiles are removed. All company information is checked and enriched with the help of AI to ensure you have all the necessary data at hand.

Employee data

Our clean dataset of employees consists of over 459 million up-to-date candidate profiles. Duplicate and incomplete profiles are removed. Employee data records are enriched with taxonomy-related data fields. 

Time-saving features

Reduced dataset size

Our clean dataset size is around 4 times smaller compared to regular raw datasets.

Less data engineering needed

You can save a significant amount of data engineering resources with clean data.

Quicker data processing

Clean datasets are easier to ingest and process.

Shorter time to value

Onboarding with a new data vendor can take months. A simplified data structure makes it much easier to get started.

Enriched data fields

Thanks to AI-driven enrichment, you get 20+ additional data points and the existing ones are improved.

Convenient formats and delivery

Multiple data formats (Parquet, JSON, JSONL, or CSV) and flexible delivery frequency (quarterly, monthly, or weekly).

Get clean data via API

One of the ways to get access to our clean datasets is by using a highly scalable API. Submit a trial request and test it for free!

AI-powered data enrichment

The data you’re getting is not only clean, but also supplemented with additional data not available in the raw version of our datasets. Clean dataset contains 20+ additional data fields. Some of these data fields are created or enriched with the help of LLM technology.

Coresignal’s raw vs. clean datasets

Features Raw data Clean data
Structured/unsructured data Structured data Structured data
Filtering Dataset contains all scraped profiles. Dataset contains complete, high-value profiles. A significant portion of duplicates and incomplete profiles are filtered out.
Standardization of values No Data values like dates and location are standardized
Text field cleaning No Stylistic code tags and special characters are removed, multiple spaces are changed to single spaces, trailing special characters are trimmed/removed.
Data points Dataset contains data points that are present in the source and metadata. Dataset contains most of the data points that are present in the source, meta data, and additional data points.
Data enrichment Data is not enriched Data is enriched
Data formats Available in JSON, JSONL, and CSV Available in JSON, JSONL, CSV, and Parquet format

Why 400+ companies choose Coresignal

Dedicated account managers

Get the most out of your clean dataset with the help of a dedicated account manager. We value long-term relationships and strive to provide quick support.

In the market since 2016

Our team includes some of the most experienced web data extraction professionals. The advanced infrastructure they built over the years allows us to expand our datasets daily.

Responsible data collection

We offer data in multiple formats, flexible delivery frequency and ensure transparent information about data operations to our clients.

But don’t take us at our word.
Listen to our clients.

Find more reviews on Datarade.

Start Quote

We are using Coresignal to enrich our AI platform for Sales Pipeline Growth. We proactively recommend sales-ready opps, interested buyers, warm intros, and trusted actions, which results in +25% in net new pipeline in 2 months, and +40% after 6 months.

Lead generation client

Before we started working with Coresignal, the percentage of investments that we made that had data influence was around 2% and currently it's around 65%.

Venture capital client

We chose Coresignal because of the coverage, data freshness, and ability to extend to other data sources.

Sales tech client

End Quote

Find more reviews on Datarade.

Frequently asked questions

What is clean data?

Clean data is a refined and enhanced version of our raw datasets. Currently, we offer two clean datasets: employee dataset and company dataset.

What are the key differences between Coresignal's raw and clean data?

The key differences are:

  • Data processing level
  • Dataset size
  • Number of available data points
  • Data enrichment

For a more detailed comparison, refer to the section Coresignal’s raw vs. clean datasets above.

What delivery frequency options are available?

Quarterly, monthly, and weekly.

Who uses clean data?

Companies that don't have the required resources or don't want to clean and process raw data themselves.


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