Sealed Inference: A New Standard for Cryptographically Private AI

The rapid advancement of Artificial Intelligence (AI) has brought both excitement and concern. As AI coding agents increasingly access entire codebases, the need for a secure and private infrastructure becomes more pressing than ever. Enter Sealed Inference, a groundbreaking security architecture developed by 0G Labs, which promises to deliver what centralized AI platforms cannot: privacy enforced by code, not corporate policy.

Sealed Inference is a crucial component of 0G's decentralized AI operating system (dAIOS), designed to provide a secure and transparent environment for building AI applications. With the introduction of this innovative technology, 0G Labs aims to address the pressing issue of data breaches and protect sensitive information from unauthorized access.

The current state of AI privacy is characterized by a reliance on corporate policy and trust in node operators. This approach has proven inadequate, as centralized providers expect users to trust their policies, while decentralized platforms rely on users' trust in their node operators. In contrast, Sealed Inference takes a fundamentally different approach: privacy by code, verified on every call.

Here's how it works:

* Every inference provider on the 0G Compute Network runs inside a Confidential Virtual Machine (CVM) powered by Intel TDX processors and NVIDIA H100 or H200 GPUs operating in Trusted Execution Environment (TEE) mode. * User prompts enter encrypted and are processed in complete isolation, with the machine owner unable to inspect, copy, or modify data during computation. * A cryptographic signing key pair is generated inside the TEE upon provider startup, with the private key never leaving the secure enclave. * CPU and GPU attestation reports bind the public key to the TEE environment, creating a verifiable chain that proves the key was born inside genuine secure hardware — not emulated or spoofed. * Every AI model response is cryptographically signed with the provider's enclave-born key before it reaches the user.

This approach ensures that every inference call carries built-in proof: proof of processing within a real TEE, proof of no tampering during execution, and proof of authentic responses. Users can also download Remote Attestation (RA) reports at any time to independently verify any provider's security posture.

Sealed Inference has been integrated into 0G's Compute Network, which is currently live on mainnet, powering AI inference across large language models — including GLM-5, one of the most capable open-source reasoning models available — as well as vision-language, speech-to-text, and image generation services. All verified through Sealed Inference.

Developers can integrate with the technology using a Web UI, CLI, or TypeScript SDK with transparent per-token pricing. Additional verification methods, including OPML and ZKML, are in active development.

The AI industry is entering a phase where models don't just answer questions — they operate inside the most sensitive environments a business has. When an AI agent can read your entire codebase, modify your infrastructure, and access your credentials, the question isn't whether the provider's privacy policy is well-written. The question is whether privacy is enforced by the architecture itself.

Sealed Inference replaces trust with mathematics — privacy by code, verified on every call. As Aytunc Yildizli, 0G's Chief Growth Officer, puts it: "AI agents read your entire codebase now. Your source code, your keys, your business logic. Privacy at that level can't be a policy promise. It has to be enforced by the architecture. That's what Sealed Inference does: the hardware itself prevents anyone from seeing your data during processing. Not us, not the node operators, not anyone."

Sealed Inference is one component of 0G's dAIOS — a full-stack decentralized AI operating system designed to provide a secure and transparent environment for building AI applications. With Sealed Inference, 0G Labs aims to address the pressing issue of data breaches and protect sensitive information from unauthorized access.

As the AI industry continues to evolve, it is crucial that we prioritize privacy and security. Sealed Inference offers a promising solution, providing a new standard for cryptographically private AI. By harnessing the power of mathematics and code, 0G Labs is redefining the way we approach AI development and deployment.

Conclusion

Sealed Inference is a groundbreaking innovation in the field of AI privacy. By leveraging cutting-edge technology and cryptography, 0G Labs has developed a solution that promises to protect sensitive information from unauthorized access. As the AI industry continues to grow and evolve, it is essential that we prioritize privacy and security. Sealed Inference offers a promising solution, providing a new standard for cryptographically private AI.

By embracing this technology, we can ensure that AI applications are built with security and privacy in mind. This will not only protect sensitive information but also build trust between users and providers. As the AI landscape continues to shift, it is crucial that we prioritize innovation and security. Sealed Inference is a step in the right direction, and we look forward to seeing its impact on the industry.