OpenMined develops privacy-enhancing technologies and open-source software — including PySyft, SyftBox, and SyftHub — that create a public network for non-public information. Founded in 2017 by Andrew Trask, the organization enables federated learning, secure multi-party computation, homomorphic encryption, and trusted execution environments to allow AI audits, research collaboration, and data sharing without centralizing or exposing sensitive information. OpenMined has partnered with major institutions including the UK AI Safety Institute, Anthropic, Microsoft, Twitter/X, the United Nations, the World Health Organization, and NIST's NAIRR Pilot to deploy this infrastructure at scale.
Funding Details
- Annual Budget
- $2,388,315
- Monthly Burn Rate
- $199,026
- Current Runway
- -
- Funding Goal
- -
- Funding Raised to Date
- $10,000,000
- Fiscal Sponsor
- -
Theory of Change
OpenMined believes that a key precondition for AI safety and governance is the ability to audit and evaluate AI systems independently — without requiring AI developers to grant direct access to sensitive models, training data, or user information. By building open-source infrastructure for privacy-preserving computation (secure enclaves, federated learning, homomorphic encryption, multi-party computation), OpenMined enables governments, researchers, and civil society organizations to ask questions of AI systems and verify safety-relevant claims without the AI developers being able to hide or obscure dangerous capabilities. If this infrastructure is widely deployed and adopted, it creates the technical substrate for meaningful external oversight and accountability of AI systems — a structural safeguard against misuse, capability concealment, or misaligned behavior at scale.
Grants Received
from Open Philanthropy
from Open Philanthropy
from Open Philanthropy
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Details
- Last Updated
- Apr 2, 2026, 10:10 PM UTC
- Created
- Mar 20, 2026, 2:34 AM UTC