Blog
Insights on software provenance, security, and compliance.
Model Card Best Practices for SOC 2 Mapped AI Vendors
Learn how to build model cards that satisfy SOC 2 audits and EU AI Act requirements with technical, evidence-driven documentation.
AI Bill of Materials: The 7 Fields Auditors Will Look For First
Ensure compliance with the EU AI Act and SOC 2 by implementing these 7 essential AI Bill of Materials fields for model provenance and security.
AI Vendor Due Diligence Checklist for 2026 Procurement Teams
Enterprise checklist for AI vendor evaluation: compliance artifacts, provenance evidence, security controls, and audit-ready documentation for 2026.
What Is AI Model Provenance and What Audit Teams Ask For
AI model provenance is a record of how a model was trained, what data it used, and which components it depends on. Audit teams often ask for that record. This article describes the fields they look for. It is not a statement that any regulator requires a specific document.
Investor Ready MVP Checklist: Security, Compliance, and Provenance Evidence
Investors want proof that your MVP is production-ready. This checklist covers the security, compliance, and provenance evidence that separates fundable products from science projects.
How AI-Origin Detection Works: Signal Types Explained
AI-origin detection combines stylometry, entropy, dependency context, and commit history to estimate whether code was human-written, AI-assisted, or AI-generated.
EU AI Act Compliance for Engineering Teams: A Practical Guide
Engineering teams can prepare for EU AI Act obligations by documenting AI-assisted code, dependency lineage, risk classifications, and human review decisions.
What Is Software Provenance? A Complete Guide for Security Teams
Software provenance tracks the origin, history, and integrity of every component in your codebase. Learn why it matters for supply chain security and how to implement it.