Tumult Analytics
The enterprise-grade differential privacy platform.
Overview
Tumult Analytics is a Python library and enterprise platform that makes it easier and safer to use differential privacy. It is designed to be robust, easy-to-use, scalable, and expressive. The open-source version of Tumult Analytics is now part of the OpenDP project. Tumult, the company, also offers an enterprise-grade platform that helps organizations publish sensitive data with strong, provable privacy guarantees. It is used by institutions like the U.S. Census Bureau and the IRS.
✨ Key Features
- Open-source Python library for differential privacy
- Enterprise platform for production use cases
- Scalable to large datasets
- Familiar, easy-to-use API
- Advanced privacy accounting
🎯 Key Differentiators
- Enterprise-grade platform with support
- Proven in production at large government agencies
Unique Value: Offers a robust and scalable platform for applying differential privacy in enterprise environments, with a proven track record of use in high-stakes applications.
🎯 Use Cases (4)
✅ Best For
- Used by the U.S. Census Bureau, Wikimedia, and the Internal Revenue Service for publishing sensitive data.
💡 Check With Vendor
Verify these considerations match your specific requirements:
- Simple, one-off analyses on non-sensitive data where the overhead of differential privacy is not necessary.
🏆 Alternatives
While open-source libraries provide the building blocks, Tumult offers a complete enterprise solution with support and features designed for production use cases.
💻 Platforms
✅ Offline Mode Available
🔌 Integrations
🛟 Support Options
- ✓ Email Support
- ✓ Dedicated Support (Enterprise tier)
💰 Pricing
Free tier: The open-source library is free to use.
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