Empowering Privacy-Preserving Collaboration

SyftBox [Beta] is an open-source protocol that enables developers and organizations to build, deploy, and federate privacy-preserving computations seamlessly across a network. Unlock the ability to run computations on distributed datasets without centralizing data—preserving security while gaining valuable insights.

Here's how SyftBox can benefit you:

Simplified Development

Build and deploy privacy-preserving applications with ease, regardless of your programming language or environment.

Increased Collaboration

Securely share data and collaborate with partners, researchers, and even competitors while upholding privacy.

Improved Trust

Foster trust and transparency with a secure and auditable framework for responsible data handling.

Privacy by Design

Keep full control of your data within the decentralized network—secure, untouched, and only accessed with your consent.

What Can You Do with SyftBox?

SyftBox has been used to:

Build Privacy-Preserving AI Models Across Distributed Data

Train machine learning models on sensitive datasets without moving or exposing the data—enabling secure AI innovation across multiple organizations.

Run Secure Analytics Without Accessing Raw Data

Perform analysis on private datasets held by different parties, extracting insights while ensuring data remains remains at the source and kept confidential.

Collaborate Across Organizations Without Trust Assumptions

Work with partners, competitors, or researchers on shared computations without ever relinquishing data control.

Enable Individuals to Contribute Data Without Sacrificing Privacy

Power a decentralized ecosystem where users can securely contribute their data to research and applications while retaining full ownership and consent.

Access Orders of Magnitude More Data Without Centralization

Leverage a growing network of privacy-preserving data collaborations, making it easier to work with more data sources while maintaining security and compliance.

SyftBox is ideal for:

Data Engineers

seeking to build privacy-preserving applications without specialized expertise.

Researchers

who need to analyze sensitive data or train AI models without direct data access.

Businesses

looking to collaborate on data-driven projects while protecting confidential information.

How it Works

1: Install

Download and install the SyftBox client to connect to the decentralized network.

2: Browse

Explore the network to find datasets and privacy-preserving applications and APIs offered by various data owners.

3: Request

Ask a data owner to run any API—yours or others—on their data. Optionally, connect and make your data discoverable.

4: Analyze

Once approved, utilize the API to perform computations and extract insights from the data without compromising its privacy.

Key Features:

Network-First Architecture

Enables seamless collaboration and data sharing across multiple parties with strong privacy boundaries.

Language & Environment Agnostic

Supports a wide range of programming languages and development environments for maximum flexibility.

Modular & Extensible

Easily adapt and extend the platform to meet your specific needs.

Secure Data Storage & Management

Provides secure and efficient mechanisms for storing and managing sensitive data.

Ready to experience privacy-preserving collaboration?

Visit the SyftBox documentation to started today!

SyftBox Documentation

Join the Beta Access group

Want to keep up with the latest? Sign up here.