en.Wedoany.com Reported - On March 31, 2026, Hammerspace, based in Redwood City, California, announced that its data platform will support FIPS 140-3 validated encryption technology to meet U.S. government cryptographic security standards. This advancement enables the platform to be deployed in highly regulated sectors such as federal, defense, healthcare, and finance. The integration is planned for implementation in a release version before the end of 2026.

Molly Presley, Senior Vice President of Global Marketing at Hammerspace, stated: "This validation is a critical milestone for government and other security-sensitive deployments. The greater challenge is maintaining control over distributed data across data centers, clouds, and edge environments without sacrificing performance or flexibility. This is precisely where Hammerspace differentiates itself. We built the platform to secure, govern, and orchestrate data at the data layer itself—providing the foundational infrastructure organizations need for large-scale artificial intelligence."

By integrating FIPS 140-3 validated encryption, the Hammerspace data platform aims to enforce security at the data layer, ensuring consistent control, compliance, and data sovereignty. The platform provides policy-driven orchestration, governance, and protection in distributed environments, supporting multi-site and hybrid cloud architectures.

Platform capabilities include end-to-end encryption with FIPS-validated security, built-in data protection and ransomware resilience, consistent security enforcement within a global namespace, unified access control across protocols and environments, and policy-driven data governance, sovereignty, and orchestration. FIPS 140-3, defined by the U.S. National Institute of Standards and Technology, sets stringent standards for cryptographic modules, requiring independent testing for validation, and is mandatory for federal agencies and compliant organizations.

The Hammerspace data platform is a high-performance solution designed to simplify and optimize large-scale AI infrastructure, making data immediately accessible across on-premises and cloud environments without replication or migration. By integrating existing storage, networking, and applications, it creates a unified data backbone for AI, accelerating AI pipelines and eliminating data silos.

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