AI Auditing: From "Trust Us" to "Mathematically Verifiable" — GhostDrift Releases Formal Proof of ADIC

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Saving "evidence of what AI did" in a way that anyone can reproduce and verify using the same procedure later — this is the third-party verifiable AI governance foundation required by the EU AI Act. GhostDrift Mathematical Research Institute has released a formal proof, verifiable in Lean 4, for the replay verification theory, which is at the core of "ADIC (Advanced Data Integrity by Ledger of Computation)," a technology that preserves AI judgments as evidence that can be re-executed and verified by third parties. ADIC fundamentally differs from conventional audit logs in that it preserves not only the result of a judgment but also the process leading to that judgment as evidence. In high-responsibility domains such as logistics, pharmaceuticals, finance, and the public sector, where AI judgments directly lead to accidents, significant losses, or administrative decisions, if it is not possible to explain "why that judgment was passed" after the fact, an "evaporation of responsibility" occurs where no one can take responsibility. ADIC is a foundation that prevents such situations where "everyone was supposed to be right, but a problem occurred," enabling companies and organizations to take definite responsibility for AI. The structure of "evaporation of responsibility" that ADIC prevents In Europe, the full application of the EU AI Act, which can impose penalties of up to 7% of the previous year's worldwide annual turnover for serious violations, is approaching on August 2, 2026. The level of demand for AI governance is globally shifting from the conventional stage of operating with strict internal rules to the stage of presenting evidence that can be verified by independent third parties. The formal proof released this time makes the concept of "replay verification," which is at the core of ADIC, reproducible and verifiable by third parties on Lean 4. This demonstrates that when ADIC's verifier accepts a certificate, the corresponding validity conditions hold for th

AI Auditing: From "Trust Us" to "Mathematically Verifiable" — GhostDrift Releases Formal Proof of ADIC

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