Product updates, engineering notes, and practical guides for teams building with confidential AI in defense, finance, and regulated environments.
Read how Orgn approaches secure coding environments, private LLM routing, agent governance, and audit-ready AI workflows.
What data sovereignty means for AI coding tools in 2026—residency vs. sovereignty, five requirements for regulated enterprises, and why policy promises are not enough.
An 8-step procurement checklist for security teams evaluating AI coding tools in 2026—data retention, TEE isolation, attestation, compliance, and vendor scoring.
How Origin Gateway routes AI inference between standard zero data retention LLMs and Intel TDX confidential execution—with sensitivity-based routing and cryptographic attestation.
A structured framework for CISOs evaluating AI coding tools in regulated enterprises—execution isolation, attestation evidence, and why most tools fail security reviews.
Confidential computing uses hardware-isolated TEEs to protect code during AI-assisted development. Learn why policy-based security fails regulated reviews and what verifiable proof looks like.
Zero data retention is necessary for AI coding tools in regulated environments—but policy commitments are not proof. Learn what ZDR means and how to evaluate vendor claims.
Cryptographic attestation turns security claims into verifiable facts. A plain-English guide for security teams evaluating AI coding tools in regulated environments.