Tinfoil
Tinfoil is a verifiably private AI platform built to deliver zero-trust, zero-data-retention inference by running open-source or custom models inside secure hardware enclaves in the cloud, giving you the data-privacy assurances of on-premises systems with the scalability and convenience of the cloud. All user inputs and inference operations are processed in confidential-computing environments so that no one, not even Tinfoil or the cloud provider, can access or retain your data. It supports private chat, private data analysis, user-trained fine-tuning, and an OpenAI-compatible inference API, covers workloads such as AI agents, private content moderation, and proprietary code models, and provides features like public verification of enclave attestation, “provable zero data access,” and full compatibility with major open source models.
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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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Confidential AI
Confidential AI provides private inference, private agents, confidential VMs and confidential computing infrastructure for AI labs, inference providers, routers, and organizations handling sensitive workloads. Its hosted inference service runs open-weight models in hardware-backed trusted execution environments (TEEs), including Intel TDX and AMD SEV-SNP confidential VMs with NVIDIA GPUs in confidential computing mode. Prompts, responses, and workload data are protected from infrastructure operators, and clients can verify attestation before sending sensitive input. Customers can use an OpenAI-compatible API to deploy inference endpoints and agent workloads, or license the confidential-computing stack for on-premises infrastructure, bare metal, and major clouds. Use cases include serving models while limiting operator access to prompts and model assets, and running sensitive AI workloads on dedicated confidential compute.
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Phala
Phala is a hardware-secured cloud platform designed to help organizations deploy confidential AI with verifiable trust and enterprise-grade privacy. Using Trusted Execution Environments (TEEs), Phala ensures that AI models, data, and computations run inside fully isolated, encrypted environments that even cloud providers cannot access. The platform includes pre-configured confidential AI models, confidential VMs, and GPU TEE support for NVIDIA H100, H200, and B200 hardware, delivering near-native performance with complete privacy. With Phala Cloud, developers can build, containerize, and deploy encrypted AI applications in minutes while relying on automated attestations and strong compliance guarantees. Phala powers sensitive workloads across finance, healthcare, AI SaaS, decentralized AI, and other privacy-critical industries. Trusted by thousands of developers and enterprise customers, Phala enables businesses to build AI that users can trust.
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