Replayable Consequences.

Insurance claim replay is one expression. So are regulatory enforcement reconstruction, fraud-event reconstruction, cyber-incident response, financial-loss adjudication, operational-failure root-cause analysis, and AI-decision review. All of them are the same question: when something consequential happens, can you reconstruct everything around it — independently, verifiably, and at a time horizon long enough to matter?

Today, the answer is almost always no. Logs are operator-attested. Reconstructions are post-hoc narratives. Witnesses leave the company. Vendors are acquired. Original systems are replaced. The trail goes cold long before the consequence is resolved.

For any consequential decision or event, H33 Consequence Replay reconstructs:

• What happened — the action itself, cryptographically committed at the moment of execution
• Why it happened — the inputs, policies, and triggering conditions that produced the action
• Who approved it — every signer's role and authority at the moment of approval
• What policy governed it — the exact policy version hash-locked at decision time
• What model influenced it — the AI or ML model identity, version, and inputs
• Who retained responsibility — the accountability chain, including delegation provenance
• What loss resulted — the realized outcome, bounded and quantified
• Who else was affected — the downstream parties and consequent obligations

Each dimension is cryptographically committed at the moment of the event and verifiable offline by any party with the receipt — including parties who don't trust the operator, don't have access to the original systems, and weren't present when the event occurred.

Insurance claim adjudication — was the policy in force, were the controls operating, was the loss bounded by the coverage? See Insurance Claim Replay for the specific application.

Regulatory enforcement reconstruction — what did the firm know, when did they know it, what controls were active, who had authority to act, what was actually done?

Fraud-event reconstruction — which signatures were valid, which were forged, who had authority to authorize each step, where did the chain break?

Cyber-incident response — what was the configuration at the moment of compromise, did the controls operate as represented, what was actually exfiltrated?

Financial loss adjudication — who is responsible, in what proportion, under what policy or contract, with what evidentiary basis?

Operational failure root-cause — what was the system state, which decisions led to the failure, where did the accountability sit, what changes were made after?

AI decision review — what model produced the decision, what were its inputs, what policy constrained it, who approved its deployment, can the decision be reproduced?

Every consequential decision produces a 74-byte H33-74 attestation receipt at the moment of execution. The receipt is signed under three independent post-quantum signature families (ML-DSA, FALCON, SLH-DSA) and bound to the organizational policy state, the model state, the authority chain, and the input commitment.

Years later, when the consequence becomes adjudicable, the H33 replay tooling reconstructs the full event from the receipt — without re-running the original computation, without contacting the operator, without trusting any intermediate party. The open verifier (github.com/H33ai/h33-verifier, Apache 2.0) runs anywhere and produces a deterministic verdict.

Hundreds of millions of AI agents will produce trillions of consequential decisions over the next decade. The first wave of those decisions is already producing losses, regulatory actions, civil suits, and insurance claims. None of the current AI infrastructure produces evidence that can be re-verified by the affected parties.

Consequence Replay is the cryptographic substrate that closes that gap. Not for one use case — for the whole class. Insurance is the first commercial expression. Regulation, litigation, and operational accountability follow.