Yes. Every regulated industry deploying AI in consequential decisions faces existing audit obligations. Health systems, financial institutions, autonomous vehic
AI decision integrity is not a speculative market. It is defined by existing regulatory frameworks that already require auditable decision records in healthcare (HIPAA, FDA SaMD), financial services (SOX, ECOA, SR 11-7), autonomous vehicles (NHTSA), and manufacturing (ISO 9001, FDA 21 CFR Part 820).
What is new is that AI is now making the decisions that these frameworks were designed to govern. The regulations were written for human decision-makers, but AI systems are increasingly taking on those roles. The gap between regulatory requirements and technical capabilities is the market opportunity.
Organizations do not need to wait for regulators to mandate cryptographic proof. The immediate value proposition is liability defense. A hospital using AI for radiology triage today has malpractice exposure today. A financial institution using AI for credit decisions faces fair lending scrutiny today. InferTrust™ is not preparation for future regulations. It is protection against lawsuits and examinations that are happening now.
Cloud providers can build server-side logging, and many already have. But device-bound signing with non-extractable hardware keys is architecturally incompatible with cloud-first models. The core innovation of InferTrust™, signing at the point of inference on the local device, requires a fundamentally different approach that cloud infrastructure cannot replicate.