OpenMined

After nearly a decade of R&D, PySyft has been used by GDM, AVERI, Singapore AISI, and MLCommons to facilitate the world's first double-blind evaluations of a proprietary, frontier class AI model.

PETs offer U.S. critical-infrastructure AI a path beyond patchwork security. Why Attribution-Based Control should be the standard.

The future of AI isn't total ingestion or today's disordered muddle. Network sourced AI offers a third path: private repositories titrating insights under conditions their stewards define.

OpenMined shares a year-two update on its partnership with the NAIRR, including the launch of a Deep Partnership with Indiana University for privacy-preserving medical text de-identification.

Blocking AI crawlers, licensing, and paywalls can't protect publisher content. Learn why current defenses fail and how the Syft Protocol offers a new path

OpenMined participated in the 2026 India AI Impact Summit in New Delhi, demonstrating BioVault for privacy-preserving genomics research and contributing to policy discussions on data sovereignty, conditional openness, and the "Visit, Don't Move" paradigm

OpenMined brings privacy-preserving genomics infrastructure to India AI Impact Summit 2026 in New Delhi, partnering with Human Genome Project II (HGP2).

OpenMined joins Carnegie Mellon University's Open Forum for AI (OFAI) to contribute expertise in privacy-preserving data access to the initiative's Data Working Group, advancing responsible and human-centered AI development

ACM's flagship publication highlights OpenMined's Attribution-Based Control as a solution for governing synthetic data and ensuring transparency in AI training.

Run a complete federated learning workflow in Google Colab-no local setup. Train models across private datasets with syft-flwr while data stays put.