Confidential computing protects data while it's being processed — the last gap in the encryption story. This guide explains how it works, the hardware that powers it, real-world use cases, and how to adopt it without rewriting your applications.
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97% of enterprise AI deployments are blocked by 'no sensitive data in LLMs' policies. This guide covers exactly how to unlock AI on PII, PHI, and financial data using hardware-isolated enclaves — with cryptographic proof your data never left the boundary.
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AI agents don't need to carry your users' personal data through every step of a workflow. Here's how to enforce field-level PII stripping at each step boundary — with an audit log that proves it.
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Zero-knowledge proofs let users prove identity claims without revealing underlying PII. Trusted Execution Environments let verifiers prove the check ran correctly without trusting the operator. Together, they form a compliance architecture that enterprises and AI agents can actually trust.
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Most Docker images carry far more than your application needs — extra packages, root access, known CVEs. Hardened images strip that attack surface away. Here's what they are, how to build them, and why they're non-negotiable for production security.
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As AI agents gain autonomy, someone has to govern them. An AI control plane is the policy, identity, and observability layer that sits above your agents — ensuring they run exactly as intended, on verified infrastructure, with cryptographic proof.
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A practical guide to the security and compliance standards — FIPS 140-3, ISO 27001, SOC 2, NIST 800-53, PCI DSS, and more — that privacy-first platforms should align with, and how TEE-based architectures like Treza map to each.
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AI agents can write code and manage infrastructure, but most still need a human to set up billing. This tutorial shows how to build an agent that discovers, pays for, and consumes APIs autonomously — using x402 micropayments and hardware-secured wallets.
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Multi-Party Computation, Trusted Execution Environments, and Fully Homomorphic Encryption each solve privacy differently. This guide compares performance, trust assumptions, and practical deployment so you can pick the right one for your use case.
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Every AI API call sends your data to someone else's server. This guide covers the full spectrum of private AI approaches — from local inference to hardware-isolated enclaves — and shows how to run production AI workloads where not even the cloud operator can see your prompts or outputs.
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A practical guide to running Docker containers inside secure enclaves. Learn how to deploy, attest, and manage workloads in AWS Nitro Enclaves without rewriting your application — using the Treza SDK, CLI, or REST API.
Read More→Trusted Execution Environments provide hardware-level isolation for sensitive computation. This guide explains how TEEs work, compares AWS Nitro Enclaves vs Intel SGX vs AMD SEV, and shows when your application needs one.
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Treza now supports the x402 protocol — AI agents can discover, access, and pay for secure enclave services using instant USDC micropayments on Base. No API keys, no subscriptions, no human in the loop.
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Deploy OpenClaw, the open-source personal AI assistant, inside a hardware-isolated Trusted Execution Environment using Treza's Nitro Enclave infrastructure. Full walkthrough from Docker image to cryptographic attestation.
Read More→AI assistants handle API keys, messaging credentials, and user conversations. A Trusted Execution Environment enforces hardware-level isolation that Docker and VMs cannot match. Here's what TEEs are, why they matter, and how to run OpenClaw inside one.
Read More→Step-by-step guide to running OpenClaw, the open-source AI assistant, in a Docker container. Covers installation, configuration, Telegram setup, dashboard access, and production hardening.
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Hardware-protected cryptographic key management and signing operations with enterprise-grade security and compliance guarantees.
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Deploy autonomous agents and smart contracts that execute independently with cryptographic guarantees inside secure enclaves.
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Handle protected health information with compliant secure enclaves that meet HIPAA regulatory requirements.
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Meet regulatory requirements with verifiable cryptographic compliance powered by hardware-isolated secure enclaves.
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Process sensitive media content in secure enclaves with end-to-end encryption and hardware-level isolation.
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Privacy-preserving identity verification with multi-tier compliance levels. Verify age, nationality, and document validity on-chain without exposing personal data.
Read Docs→Tell us what your agent does (or should do). In 20 minutes we’ll sketch the runtime, the keys it needs, and what production looks like. No pitch deck.
