Venn
Venn is the leader in BYOD Security. Venn’s Blue Border™ is patented technology that protects company data and applications on BYOD computers used by contractors and remote employees - without VDI.
With Venn, work lives in a company-controlled Secure Enclave (installed on the user’s PC or Mac) where all data is encrypted and access is managed. Work applications run locally within the Enclave (no hosting or virtualization) and are protected and isolated from any personal use on the same computer.
With Venn, customers are empowered to achieve the cost savings and workforce agility of BYOD, while ensuring robust data protection and compliance with HIPAA, FINRA, PCI, SOC 2, and many more.
Join the 700+ organizations, including Fidelity, Guardian, and Voya, that trust Venn to secure their business-critical data and apps.
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Google Cloud Confidential VMs
Google Cloud’s Confidential Computing delivers hardware-based Trusted Execution Environments to encrypt data in use, completing the encryption lifecycle alongside data at rest and in transit. It includes Confidential VMs (using AMD SEV, SEV-SNP, Intel TDX, and NVIDIA confidential GPUs), Confidential Space (enabling secure multi-party data sharing), Google Cloud Attestation, and split-trust encryption tooling. Confidential VMs support workloads in Compute Engine and are available across services such as Dataproc, Dataflow, GKE, and Gemini Enterprise Agent Platform Notebooks. It ensures runtime encryption of memory, isolation from host OS/hypervisor, and attestation features so customers gain proof that their workloads run in a secure enclave. Use cases range from confidential analytics and federated learning in healthcare and finance to generative-AI model hosting and collaborative supply-chain data sharing.
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NVIDIA Confidential Computing
NVIDIA Confidential Computing secures data in use, protecting AI models and workloads as they execute, by leveraging hardware-based trusted execution environments built into NVIDIA Hopper and Blackwell architectures and supported platforms. It enables enterprises to deploy AI training and inference, whether on-premises, in the cloud, or at the edge, with no changes to model code, while ensuring the confidentiality and integrity of both data and models. Key features include zero-trust isolation of workloads from the host OS or hypervisor, device attestation to verify that only legitimate NVIDIA hardware is running the code, and full compatibility with shared or remote infrastructure for ISVs, enterprises, and multi-tenant environments. By safeguarding proprietary AI models, inputs, weights, and inference activities, NVIDIA Confidential Computing enables high-performance AI without compromising security or performance.
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vp.net
vp.net is a privacy-focused VPN service built on a zero-knowledge architecture and hardware-enforced security that delivers verifiable, end-to-end encrypted connections in which even the service provider cannot identify user activity. It leverages Intel SGX enclaves and attestation services to ensure code execution is genuine and auditable, offering users immutable proof that no logs are maintained and no user data is splintered from their secured session. Performance is optimized via advanced packet-routing technology, which claims markedly faster speeds compared to competitors, while full control is retained locally on the device, ensuring network traffic is anonymized, and any metadata collection is cryptographically impossible. It is designed so that the only entity with visibility into a user’s session is the user themselves, and operations are transparent and verifiable rather than simply promised.
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