Use case

Safe Sensitive Data Sharing with Gretel

Unblock key digital initiatives with high-quality synthetic data.
Create highly representative datasets with mathematical guarantees of privacy for safe data sharing.
Safe data sharing

The data sharing challenge

Today, the vast majority of digital initiatives, from new application development and third party tool evaluation to the latest R&D are blocked by a single point of failure — lack of safe data access. These data bottlenecks, created by privacy and security concerns, stifle organizations ability to rapidly extract value from data, and prevent critical initiatives from ever taking off.As a result, data remains out of the hands of the teams that need it most and critical initiatives never take off or get stuck in innovation labs.

  • Data leaks are a looming risk

    Improper exposure of sensitive information is harmful for individuals and expensive for organizations. Traditional anonymization and de-identification methods have been shown to be  reversible.

  • Unshareable data slows innovation

    Research and development thrives on open data sharing and collaboration. Locked-up insights limit the value of data and stagnate innovation.

  • Data compliance drains time

    Compliance with GDPR, CCPA, and other privacy regulations has high administrative costs. Time spent on compliance is time not spent on development.


The Gretel data sharing solution

Gretel empowers organizations to accelerate digital innovation via safe access to synthetic data. Gretel’s platform provides teams with multiple synthetic data models as well as advanced privacy protection measures with provably private guarantees. In turn, Gretel’s synthetic data generation solution upholds the highest data security and data privacy standards, making it safe to share data across teams, environments, and applications.

Gretel Console


  • New application development

    Give developers access to safe and high-quality data to build in lower environments.

  • Safe AI training

    Train leading AI models with safe and high-quality synthetic training data.

  • Third party tool evaluation

    Evaluate third party tools with insights, not personally identifiable information.

  • Secure research and analytics

    Accelerate cross-team research, analytics, and innovation with safe data sharing.

  • Privacy sandboxes

    Empower data collaboration with secure cross-border sandboxes.


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