The regulatory, legal,and business case for cryptographic proof of AI decisions,and why organizational attestation is no longer sufficient.
As AI systems make more consequential decisions, from claims adjudication and clinical recommendations to autonomous driving and manufacturing quality control, the question is no longer whether organizations can explain what their AI did. The question is whether they can prove it.
Regulatory frameworks worldwide are shifting from "document your AI" to "prove your AI." The EU AI Act, US state-level AI transparency laws, CMS prior authorization mandates,and FDA SaMD guidance all impose requirements that go beyond having logs. They require organizations to demonstrate, with verifiable evidence, that AI decisions were made according to policy, by authorized models, with documented confidence levels.
When AI decisions are challenged in court, during appeals, or in regulatory investigations, the opposing side will question the integrity of the evidence. "How do we know these logs haven't been modified?" is a question that traditional logging cannot answer satisfactorily. Cryptographic proof answers it definitively: the mathematical signature proves the record is authentic and unaltered.
InferTrust™ (Patent Pending) is the only platform that creates cryptographically signed, tamper-evident decision records at the point of inference using device-bound keys. No AI observability tool, MLOps platform, or governance solution on the market provides this combination of execution-boundary signing, hardware-backed keys, hash-chained audit trails,and independent third-party verifiability. This is not an incremental improvement over existing tools. It is a fundamentally different approach to AI accountability.