Google has introduced a new cloud-based service called Private AI Compute, designed to deliver the same level of security as local data processing. The system enables devices to connect directly to a secure, isolated environment within Google’s AI infrastructure, ensuring that sensitive data remains protected during AI computations. Rather than processing data on a user’s device or in a shared cloud environment, Private AI Compute creates a dedicated, encrypted space in Google’s data centers. This space is isolated from other workloads and is only accessible through secure, authenticated connections from authorized devices. The approach is intended to address growing concerns about data privacy, especially in industries like healthcare, finance, and government, where regulatory requirements are strict. Google says the system uses advanced security measures, including hardware-based encryption, real-time monitoring, and strict access controls. Data is processed in memory and never written to disk, reducing the risk of exposure. Additionally, the entire computation happens within Google’s trusted cloud environment, which is built with compliance certifications and robust physical and cyber defenses. The service is particularly relevant for organizations that want to leverage powerful AI models without compromising data privacy. By allowing AI workloads to run in a secure cloud environment that mimics the safety of on-premise systems, Google aims to bridge the gap between performance and security. Private AI Compute is available to enterprise customers through Google Cloud and is designed to integrate seamlessly with existing AI workflows. Google emphasizes that while the data is processed in the cloud, it remains under the customer’s control, with full transparency and auditability. This move underscores Google’s ongoing effort to position its cloud platform as a trusted partner for AI innovation, especially in markets where data sovereignty and security are top priorities.