> For the complete documentation index, see [llms.txt](https://docs.coresignal.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.coresignal.com/employee-data/overview.md).
# Multi-source Employee Data Overview
Enriched Employee data with daily delivery of fresh data in JSONL or Parquet format. Includes historical tracking.
**Employee Data** comprises current, structured professional records created by consolidating and reconciling information from professional networking profiles, company websites, and other public sources into a single, verified employee profile.
We provide employee data through flat files or the Employee data API, mapping each field to its corresponding employee record. Our system matches and deduplicates records across sources, consolidating employee profile data, employer information, career intelligence, and social influence into a single profile.
| **Dataset of multiple sources** | Integrated multi-source data provides a comprehensive employee profile. |
| ------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| **Four data bundles** | Core employee data, employer information, career intelligence, and social influence are mapped to the same employee record, ensuring that all fields are aligned in one place. |
| **Engineering-ready data** | Employee records are delivered cleaned, enriched, and ready for use, eliminating the need for deduplication or normalization on your end. |
| **Built-in history** | Track how employee metrics change over time using historical data. |
| **Lightweight formats** | Choose JSONL or Parquet to keep file sizes smaller and speed up downloads. |
***
## Access and delivery
| Aspect | Detail |
| ------------------ | ------------------------------------- |
| Available via | Flat files and Employee Data API |
| Delivery frequency | Daily, weekly, monthly, and quarterly |
| Available formats | JSONL, Parquet |
| Scraping since | 2016-07 |
## Use cases
* **Recruitment and talent sourcing** – find qualified candidates using employee profile data, such as experience, education, and skills, as well as information about their current employers.
* **Sales and lead enrichment** – identify decision-makers and relevant prospects by combining employee data with company details such as size, industry, and revenue.
* **Talent analytics and workforce intelligence** – track career intelligence signals such as promotion rate, tenure, and recent role changes to monitor talent movement.
* **Influence and reputation research** – use social influence data and posting engagement to gauge a professional's standing and reach beyond their job title.
***
## Related sources
---
# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.
## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.
Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:
```
GET https://docs.coresignal.com/employee-data/overview.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.