Trace-AI predicts and prevents supply-chain attacks via metadata-driven analysis of open-source dependencies, registries, and maintainer activity, no source code needed. Built by engineers who scaled to millions, it helps teams ship fast and secure.
Hey everyone 👋
Trace-AI was born out of frustration and field experience.
For years, we were the ones called in after incidents, patching breaches, rebuilding trust, and realising how reactive the industry had become. Every time, the same pattern repeated: teams depended entirely on a single vulnerability database (NVD/CVE), and when it lagged or missed context, chaos followed.
That’s when we asked: What if we could see risk before it appeared in a CVE feed?
We began our research with ZSBOM, a metadata-only software bill of materials framework that analyses package registries, maintainer behaviour, and dependency metadata, no source code required. The results were eye-opening.
Metadata held the patterns that predicted most supply-chain compromises weeks before disclosure.
Trace-AI is the next step, a SaaS layer that automates this intelligence at scale. It plugs into your CI/CD or GitHub repos, continuously analyses open-source dependencies, and produces verifiable, compliance-ready risk evidence aligned with the upcoming EU Cyber Resilience Act.
Built by engineers who’ve scaled systems to millions and lived through compliance bottlenecks, Trace-AI turns software assurance from a burden into a competitive edge.
If you’re building or securing software, give it a try, no credit card, five repos free.
We’d love your thoughts, feedback, or even your toughest questions. Let’s make shipping secure the new default. 🔒🚀
