# Treza

> Treza chains the best generative models, including Veo 3.1, Sora 2, Gemini Image, Llama, and any open model, into pipelines you build visually and publish as one versioned API. One prompt can drive video, image, and text generation in a single pipeline.

## Core pages

- [Treza](https://www.trezalabs.com/): Chain the best generative models into pipelines you run from a prompt or call as an API
- [Features](https://www.trezalabs.com/features): Visual pipeline builder, versioned endpoints, run history, and guardrails
- [AI Image Generator](https://www.trezalabs.com/ai-image-generator): Text to image with Gemini Image, FLUX.2 Pro, Seedream, or any open model, as pipelines and APIs
- [Pricing](https://www.trezalabs.com/pricing): Prepaid credits that work across any model, packs start at $5
- [Developers](https://www.trezalabs.com/developers): API reference, /invoke and OpenAI-compatible endpoints, SDK quickstarts
- [Integrate](https://www.trezalabs.com/integrate): Call any published pipeline as an API, typed /invoke or OpenAI-compatible /chat/completions
- [Blog](https://www.trezalabs.com/blog): Guides and comparisons on AI video, image, and text generation pipelines
- [Contact](https://www.trezalabs.com/contact): Talk to the team about demos, enterprise plans, and volume pricing
- [Support](https://www.trezalabs.com/support): Get help with pipelines, billing, API setup, and account issues

## Blog

- [How to Add AI Voiceover to Videos with Text-to-Speech (2026 Guide)](https://www.trezalabs.com/blog/how-to-add-ai-voiceover-to-videos-text-to-speech): Learn how to add AI voiceover to videos with a text-to-speech API: turning a script into natural narration, timing it to your footage, and wiring the whole thing into a repeatable pipeline instead of recording every clip by hand.
- [How to Create a Faceless YouTube Channel (2026 Guide)](https://www.trezalabs.com/blog/how-to-create-a-faceless-youtube-channel): Learn how to create a faceless YouTube channel step by step: picking a niche, generating videos with AI, captions and metadata, auto-publishing, and monetization.
- [How to Transcribe Video Automatically with an AI Transcription API (2026 Guide)](https://www.trezalabs.com/blog/how-to-transcribe-video-automatically-ai-transcription-api): A step-by-step guide to transcribing video automatically with an AI transcription API: extract audio, run a speech-to-text model, get timestamped text and JSON, as one repeatable pipeline.
- [How to Add Captions to AI Videos Automatically (2026 Guide)](https://www.trezalabs.com/blog/how-to-add-captions-to-ai-videos-automatically): A step-by-step guide to auto-captioning AI videos: transcribe the audio, generate SRT/VTT subtitles, and burn them in, all as one repeatable pipeline behind an API.
- [How to Auto-Publish AI Videos to YouTube (2026 Guide)](https://www.trezalabs.com/blog/how-to-auto-publish-ai-videos-to-youtube): Learn how to automatically publish AI-generated videos to YouTube: the recommended resumable upload API, titles and metadata, captions, and scheduling, as one pipeline.
- [How to Get API Access to Veo 3.1 and Sora 2 (2026 Guide)](https://www.trezalabs.com/blog/veo-3-and-sora-2-api-access-guide): How to call Veo 3.1 and Sora 2 from your own code: where each API lives, what access requires, pricing gotchas, and how to use both models behind one endpoint.
- [Multi-Model AI Pipelines: How to Chain Video, Image, and Text Models](https://www.trezalabs.com/blog/multi-model-ai-pipelines-chaining-video-image-text): Learn what a multi-model AI pipeline is, common patterns for chaining video, image, and text models, and how to publish the whole chain behind one API.
- [Veo 3.1 vs Sora 2: Which AI Video Model Should You Use?](https://www.trezalabs.com/blog/veo-3-vs-sora-2-ai-video-model-comparison): A practical comparison of Veo 3.1 and Sora 2 for AI video generation: quality, motion, duration, cost, and when to pick each. Plus why you shouldn't lock yourself to one.
- [AI Agent Sandboxing: How to Contain Autonomous AI Execution in 2026](https://www.trezalabs.com/blog/ai-agent-sandboxing-hardware-isolation-containment): Software sandboxes can't contain a compromised AI agent, the escape paths are too wide. Learn how hardware-enforced isolation, attestation, and least-privilege execution boundaries create a sandbox that actually holds in production.
- [How to Build an AI Video Generation Pipeline (2026 Guide)](https://www.trezalabs.com/blog/how-to-build-an-ai-video-generation-pipeline): A step-by-step guide to building an AI video generation pipeline: turn a brief into a shot prompt with an LLM, render it with Veo 3.1 or Sora 2, and ship it behind one API.
- [Zero Trust for AI Agents: A Complete Architecture Guide for 2026](https://www.trezalabs.com/blog/zero-trust-for-ai-agents-complete-architecture-guide): Traditional zero trust assumes humans log in and log out. AI agents run continuously, hold credentials, and make autonomous decisions, the old model breaks. Learn how to apply zero trust to agentic AI systems using attestation, hardware isolation, and least-privilege design.
- [AI Agent Security: The Complete Guide for 2026](https://www.trezalabs.com/blog/ai-agent-security-production-complete-guide): AI agents that hold secrets, call APIs, and execute code introduce a fundamentally new attack surface. This guide covers the full threat model, prompt injection, secret leakage, credential abuse, and more, and the architectural defenses that actually work.
- [Prompt Injection Attacks on AI Agents: How They Work and How to Stop Them](https://www.trezalabs.com/blog/prompt-injection-attacks-on-ai-agents): Prompt injection is the top security threat for autonomous AI agents in 2026. Learn how direct and indirect attacks work, why application-level defenses fail, and how structural isolation at the execution boundary is the only reliable fix.
- [What Is Agentic AI Governance?](https://www.trezalabs.com/blog/what-is-agentic-ai-governance): Agentic AI governance is the discipline of controlling what autonomous AI agents are allowed to do, and proving what they did. Learn the risks, a six-pillar framework, and how it maps to the EU AI Act and NIST AI RMF.
- [What Is an MCP Control Plane? Governing Model Context Protocol Servers at Scale](https://www.trezalabs.com/blog/what-is-an-mcp-control-plane): MCP turned every API into a tool an AI agent can call. That's powerful, and ungoverned. An MCP control plane is the layer that decides which servers your agents can discover, which tools they can invoke, and how to prove those servers haven't been tampered with.
- [What Is Confidential Computing? A Complete Guide for 2026](https://www.trezalabs.com/blog/what-is-confidential-computing-complete-guide): 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.
- [How to Run AI on Sensitive Data Without Violating HIPAA or GDPR](https://www.trezalabs.com/blog/how-to-run-ai-on-sensitive-data): 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.
- [Redacting PII at the Step Boundary: Least-Privilege Data Access for AI Agents](https://www.trezalabs.com/blog/redacting-pii-in-agentic-systems-least-privilege-data-access): 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.
- [ZK KYC in a Trusted Execution Environment: Cryptographic Identity for the Agentic Era](https://www.trezalabs.com/blog/zk-kyc-in-a-trusted-execution-environment): 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.
- [What Are Docker Hardened Images and Why Do They Matter?](https://www.trezalabs.com/blog/docker-hardened-images-production-security): 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.
- [What Is an AI Control Plane?](https://www.trezalabs.com/blog/what-is-an-ai-control-plane): An AI control plane is the governance, policy, and audit layer above autonomous AI agents. Learn what it does, how attestation works, and when you need one.
- [FIPS, ISO, and the Compliance Standards That Matter for Privacy Infrastructure](https://www.trezalabs.com/blog/fips-iso-and-compliance-standards-for-privacy-infrastructure): 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.
- [How to Build an AI Agent That Can Pay for Its Own APIs](https://www.trezalabs.com/blog/how-to-build-an-ai-agent-that-can-pay-for-its-own-apis): 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.
- [MPC vs TEE vs FHE: Which Privacy Technology Should You Use in 2026?](https://www.trezalabs.com/blog/mpc-vs-tee-vs-fhe-which-privacy-technology-should-you-use): 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.
- [Private AI: How to Run Models Without Exposing Your Data](https://www.trezalabs.com/blog/private-ai-how-to-run-models-without-exposing-your-data): 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.
- [Secure Enclaves for Developers: Deploy Docker Containers in Hardware Isolation](https://www.trezalabs.com/blog/secure-enclaves-for-developers-deploy-docker-containers-in-hardware-isolation): 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.
- [What Is a Trusted Execution Environment (TEE)? A Complete Guide for 2026](https://www.trezalabs.com/blog/what-is-a-trusted-execution-environment-tee-complete-guide): 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.
- [x402 Payment Integration: Autonomous Micropayments for AI Agents](https://www.trezalabs.com/blog/x402-payment-integration-autonomous-micropayments-for-ai-agents): 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.
- [How to Run OpenClaw in a Trusted Execution Environment (TEE) with Treza](https://www.trezalabs.com/blog/how-to-run-openclaw-in-a-trusted-execution-environment-with-treza): 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.
- [Why AI Assistants Need Trusted Execution Environments: Running OpenClaw in a TEE](https://www.trezalabs.com/blog/why-ai-assistants-need-trusted-execution-environments-running-openclaw-in-a-tee): 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.
- [How to Run OpenClaw in Docker: Complete Setup Guide (2026)](https://www.trezalabs.com/blog/how-to-run-openclaw-in-docker-complete-setup-guide): 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.
- [HIPAA Compliance with Secure Enclaves](https://www.trezalabs.com/blog/hipaa-compliance-with-secure-enclaves): Handle protected health information with compliant secure enclaves that meet HIPAA regulatory requirements.

## Help

- [Connect Anthropic to Treza](https://www.trezalabs.com/help/connect-anthropic)
- [Connect Azure OpenAI to Treza](https://www.trezalabs.com/help/connect-azure-openai)
- [Connect a custom provider to Treza](https://www.trezalabs.com/help/connect-custom)
- [Connect OpenAI to Treza](https://www.trezalabs.com/help/connect-openai)