Built for Healthcare Research and Responsible AI

Prepare sensitive structured datasets for lower-risk sharing and analysis.

Privatedec helps research teams upload CSV data, apply privacy-preserving transformations, and generate controlled outputs for downstream collaboration, analytics, and AI workflows.

Designed for privacy-aware data handling with secure delivery, retention-aware workflows, and evidence-friendly reporting.

Why teams use Privatedec

  • Prepare structured datasets for safer research collaboration
  • Configure quasi-identifiers, sensitive fields, and privacy targets
  • Generate controlled outputs with downloadable reports
  • Deliver results through authenticated access and signed downloads
  • Support retention-aware handling and deletion workflows

Healthcare Research Workflows

Support lower-risk data sharing for clinical research, internal analytics, and cross-team collaboration using structured CSV datasets.

Responsible AI Data Preparation

Create privacy-aware inputs for downstream model development while keeping governance decisions visible and reproducible.

Governance and Control

Pair anonymization workflows with signed result delivery, retention-aware handling, and policy pages that support trust and review.

How it works

A simple guided workflow from upload to controlled delivery.

Privatedec guides users from upload through governed output in a workflow designed for clarity, review, and controlled access.

1
Upload and inspect

Validate CSV structure, preview data, and review detected columns before starting processing.

2
Configure privacy controls

Select quasi-identifiers, sensitive fields, and privacy parameters such as k-anonymity, l-diversity, and t-closeness.

3
Review and deliver results

Access reports, review outputs, and download processed files through authenticated and controlled delivery workflows.

Built to support trust on first review

Clear controls, visible policies, and review-friendly artifacts.
Secure handling

Authenticated access, controlled downloads, and clear session-based workflow management.

Retention-aware operations

Policy pages, deletion workflows, and retention settings make data handling expectations visible.

Evidence-friendly reporting

Processing reports and session records make workflow decisions easier to review and explain.

Healthcare and AI framing

Positioned for privacy-aware research collaboration and responsible data preparation for analytics and model training.

Important note

Privatedec is intended for privacy-aware data preparation workflows. Users should only upload datasets they are authorized to use.

For demonstrations and testing, use synthetic or appropriately de-identified data rather than real patient information.