Data as of Sep 26, 2026 · Based on 4,029,442 AI responses across 13,338 prompts · See how Parse measures this
PySyftopenmined.orgPySyft is open‑source technology that enables data scientists to analyze sensitive data without exposing raw data, by applying the principles of Remote Data Science to keep data confidential. It supports collaborative workflows via datasites where researchers submit proposals and data owners review and approve, or researchers can launch secure datasites to run compliant analyses and receive only the results, leveraging privacy‑enhancing technologies such as access control, federated learning, differential privacy, and zero‑knowledge proofs. It emphasizes strong security—often air‑gapped or VPN‑gapped—secure data serialization and manual or automated reviews, with deployments across partners like Microsoft, Dailymotion, the US Census Bureau, Istat, StatCan, and UNSD to enable research on protected data.
OpenminedPySyftThe market map · 5 of 100 labelled
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Excerpts where PySyft appeared in the AI's answer
PySyft: Maintained by OpenMined , PySyft treats remote data as if it were local via proxy objects
PySyft (OpenMined): More of a privacy-enhancing technology (PET) library than a pure infrastructure orchestrator.
Excerpts where PySyft appeared in the AI's answer
PySyft (by OpenMined) : Combines federated learning with differential privacy and encrypted computation libraries.
