SecurAI Protects LLMs with NVIDIA Confidential Computing
Inpher announces the general availability release of SecurAI, a leading solution that protects the privacy and security of user inputs on large language models....
Inpher Announces SecurAI for Trusted Execution Environments
Inpher announces SecurAI, a revolutionary approach to leveraging large language models (LLMs) and generative AI (AI) privately, securely and with complete autonomy....
Inpher Advances Roadmap In Support Of Government Privacy AI Mandates
Inpher announced the strategic advancements of their solution portfolio to align with President Biden’s Executive Order on the Secure and Trustworthy Development and Use of...
Bring Your Own Data With Inpher
Inpher launches enterprise-ready BYOD initiative for seamless secure data collaboration and AI project...
Inpher-Oracle Cloud Marketplace Partnership Offers Privacy Preserving Ai/Ml Platform
Inpher privacy-enhancing computation platform accelerates secure data collaboration and Ai initiatives on Oracle Cloud...
Inpher Was Recognized in the Gartner® Hype Cycle™ for Data…
Inpher Mentioned In Secure Multiparty Computation, Data Security As A Service And Homomorphic Encryption...
Inpher XOR Integrates with Microsoft Azure
XOR Now Runs on Azure VMs Advancing the Sensitive Data Collaboration...
Inpher presents an Innovative solution for AML/CFT at the ACPR…
Inpher participated in the ACPR Banque de France TechSprint in Paris on September 13 and demonstrated a commercial solution using the XOR Platform for banks to securely...
Inpher’s Research on Privacy-Preserving Machine Learning Published in Two Premier…
As our reliance on data grows, the need for data privacy becomes even more critical to everyone – and for businesses, an imperative. For Inpher, our focus has been on two...
Inpher Announces Strategic Partnership with In-Q-Tel
We are thrilled to announce today a strategic partnership with In-Q-Tel (IQT), a not-for-profit organization that identifies and accelerates the development and delivery of...
Privacy Challenges in Extreme Gradient Boosting
Machine learning (ML) is increasingly important in a wide range of applications, including market forecasting, service personalization, voice and facial recognition,...
How to Build Machine Learning Models with Private Data Sources…
AWS users occasionally need to perform analysis on data sources containing private or sensitive inputs. Inpher’s XOR Secret Computing Platform, available in AWS...
Inpher Wins Tech4Trust 2021 Startup Accelerator Program
Organizations today face unprecedented challenges in leveraging the data they own: access to sensitive data needs to be controlled more efficiently; authentication methods...
Inpher wins the iDASH Secure Genome Analysis Competition
Advances in biomedical analytics and AI have revolutionized modern healthcare. Predictive systems in this field allow for better medical and epidemiological research, as well...
Accelerating Moore4Medical’s Innovation: Ensuring Patient Privacy in Healthcare AI
Moore4Medical is a project pioneered by Philips, leading healthcare providers and hospitals in Europe. Inpher is one of the four Swiss companies selected by this consortium,...