Overview of Data Cleaner 🧼


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Your data never leaves your computer

The tool runs locally (Windows / macOS / Linux). Your CSV or Excel file is read entirely on your machine and is never uploaded as a whole. The only outbound connection is securely routed via HTTPS to api.foxentry.com, carrying only the individual field values you explicitly map for validation.

Local processing · No telemetry · Single egress host · Open source (Apache-2.0)

What it is

Foxentry Data Cleaner is a lightweight, self-hosted utility that validates, corrects, and enriches contact data (emails, phones, names, locations, and companies) within your own CSV/Excel files by directly querying the Foxentry REST API.

Instead of uploading sensitive customer databases to a third-party cloud service, the tool processes your data row by row on your local machine and writes the results back to a new local file. The core application logic is transparent and consists of ~1,900 lines of highly readable Python code.

Core Benefits

  • Zero File Uploads: You remain the sole controller of your datasets. Local processing eliminates the typical compliance, legal, and security hurdles associated with cloud-based bulk validation tools.
  • GDPR Compliant by Design: Only the specific string values you choose to map (e.g., an isolated email address or a phone number) are transmitted to our API.
  • No Telemetry: The application does not track user behavior or analytics. By default, no request logs are saved to your disk unless explicitly enabled for debugging purposes.
  • Fully Auditable: The tool is not a black box. Your IT and security teams can easily review the open-source codebase. Every release includes SHA-256 checksums and Sigstore attestations for strict integrity verification.
  • Zero Dependencies: It requires no complex framework or environment setups. You do not need Python installed on your system to run the pre-compiled binaries.

Quick Links & Downloads

The tool is available for all major operating systems. Simply download the standalone executable and run it:


Next step: Dive deeper into how the tool securely processes data in the Architecture & Data Flow section.