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OpenMined is a non-profit foundation that builds open-source technology infrastructure to help researchers and app developers access data and get answers without copying or directly accessing the data. It maintains Syft, a platform that enables secure, private analysis of non-public information across a public network. The OpenMined community, consisting of over 17,000 technologists, researchers, and industry professionals, contributes code and knowledge to expand data access for scientific fields and industries while protecting data privacy. The goal is to unlock 1000x more data for research and development by providing tools and a collaborative ecosystem that supports private, privacy-preserving data analysis.
Industries
Data & Analytics
AI & Machine Learning
Company Size
11-50
Company Stage
N/A
Total Funding
N/A
Headquarters
Oxford, United Kingdom
Founded
2017
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CAISI signs frontier AI testing agreements with 3 companies. May 6, 2026 3 mins read The National Institute of Standards and Technology's Center for AI Standards and Innovation, or CAISI, has signed agreements with Google DeepMind, Microsoft and xAI to support frontier artificial intelligence testing and research tied to national security efforts. As government and industry leaders expand efforts to evaluate frontier AI systems for national security applications, discussions around AI's growing role in cybersecurity continue to gain momentum. The 2026 Cyber Summit on May 21 will feature a panel discussion about the role of AI in cyber defense. Reserve your spot now! NIST said Tuesday the agreements build on previously announced partnerships that were renegotiated to align with directives from Commerce Secretary Howard Lutnick and the White House's AI Action Plan. Table of Contents How could CAISI agreements advance AI assessments? According to NIST, the agreements allow government evaluators to assess frontier AI models before public release and conduct additional testing after deployment. CAISI has completed more than 40 evaluations to date, including assessments involving unreleased AI models. Developers frequently provide models with reduced or removed safeguards to support evaluations focused on national security-related capabilities and risks. The agreements also support testing in classified environments and enable participation from evaluators across government agencies through the TRAINS Taskforce, a group of interagency experts focused on AI-related national security issues. CAISI Director Chris Fal said independent measurement science plays an important role in understanding frontier AI and related national security implications. "These expanded industry collaborations help us scale our work in the public interest at a critical moment," Fall added. What is CAISI? CAISI is a component of the Department of Commerce's NIST that serves as industry's primary liaison within the U.S. government to facilitate testing, collaborative research and development of best practices related to commercial AI tools. In March, CAISI teamed up with the nonprofit OpenMined to develop methods for evaluating AI systems while preserving data confidentiality. It also partnered with the General Services Administration to establish approaches to AI systems evaluation.
NIST's CAISI collaborates with OpenMined to develop privacy-preserving methods for AI evaluations. March 30, 2026 3 mins read The National Institute of Standards and Technology's Center for AI Standards and Innovation is teaming up with the nonprofit OpenMined to develop methods for evaluating artificial intelligence systems while preserving data confidentiality. The organizations signed a collaborative research and development agreement to utilize OpenMined's software infrastructure, including PySyft, to enable AI evaluations that adhere to security requirements and maintain scientific rigor, NIST said Friday. PySyft enables researchers to perform data science and analysis using non-public information without seeing or obtaining a copy of sensitive datasets. Balancing innovation and modernization with security as agencies increase adoption of AI will be a key topic at the Potomac Officers Club's 2026 Digital Transformation Summit, happening on April 22. The event will bring together government and industry leaders to explore how agencies are integrating AI into high-security federal environments to support various missions. Sign up today to gain insights from the figures shaping federal digital transformation. Table of Contents How is the caisi-openmined partnership intended to improve AI evaluations? By developing privacy-preserving evaluation methods, stakeholders can conduct rigorous AI evaluations to measure system performance even when underlying data, models or benchmarks cannot be shared due to intellectual property, data protection or national security constraints. According to NIST, insights from the effort will inform the agency's development of voluntary standards, best practices and recommendations for AI evaluation. The partnership builds on CAISI's prior work with the General Services Administration to provide evaluation frameworks, testing methodologies, and performance measurement tools for agencies before and after deployment in support of USAi, a governmentwide platform that accelerates agency adoption of generative AI. What is CAISI? The National Institute of Standards and Technology's Center for AI Standards and Innovation, or CAISI, serves as the U.S. government's primary interface with industry for testing and collaborative research on commercial AI systems. The organization works with federal partners to develop guidelines to improve AI security. It also evaluates AI capabilities that may pose risks to national security. The center recently launched the AI Agent Standards Initiative to promote secure, interoperable and trustworthy autonomous AI systems. Under the initiative, CAISI aims to develop industry-led AI agent standards, support community-driven open-source protocols, address security risks associated with agentic AI, and reinforce U.S. leadership in international AI governance.
Announcement: CAISI signs CRADA with OpenMined to enable secure AI evaluations. March 27, 2026 The Center for AI Standards and Innovation (CAISI) has signed a collaborative research and development agreement (CRADA) with OpenMined, a 501(c)(3) non-profit that develops open-source software infrastructure for secure computation across organizational boundaries. Under this agreement, CAISI and OpenMined will collaborate on research into privacy-preserving methods for conducting AI evaluations, enabling rigorous measurement of AI systems even when the underlying data, models, or benchmarks must remain confidential due to, for example, intellectual property concerns, data protection requirements, or national security considerations. Access to real-world or sensitive data presents a challenge for researchers as AI evaluations are increasingly intended to reflect or predict real-world deployments. It is simultaneously crucial that data is shared in a secure and decentralized manner, in order to safeguard intellectual property, encourage innovation, and maintain privacy. This collaboration will leverage OpenMined's software infrastructure, including PySyft and subsequent advances, to conduct evaluations that address both the security requirements of AI developers and data owners, as well as the scientific rigor demanded by researchers and evaluators. The insights generated from this collaboration will support NIST's efforts in AI security and applied AI evaluation. This research will inform the development of voluntary standards, best practices, and future recommendations for AI practitioners and adopters on how to effectively measure AI systems, e.g., for workforce or productivity uplift and other impacts. Released March 27, 2026
OpenMined introduces “Remote Data Science” as it believes it is the future of private data science.
Today, OpenMined is proud to announce the Beta version of a framework for differential privacy in Python OpenMined call PipelineDP, which OpenMined built in tight collaboration with Google.
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Industries
Data & Analytics
AI & Machine Learning
Company Size
11-50
Company Stage
N/A
Total Funding
N/A
Headquarters
Oxford, United Kingdom
Founded
2017
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