When your AI makes a decision — prove exactly what it said, when it said it
AI systems are making real decisions — approving loans, recommending treatments, screening candidates, drafting contracts. When those decisions are questioned months later, can you prove what the model actually produced? AI attestation creates a permanent, tamper-evident record of every AI input and output at the moment of generation.
The AI accountability gap
AI outputs influence real outcomes — hiring decisions, credit approvals, clinical recommendations, legal analysis. But when those outputs are challenged, most organizations can't produce proof of what the model actually said.
AI responses are consumed and discarded. When a decision is challenged 6 months later, the original output no longer exists.
Application logs can be edited, deleted, or lost. An auditor or court can't trust your internal logs as independent evidence.
Re-running the same prompt on the same model produces different outputs. You can't recreate what happened — you can only prove what was recorded.
EU AI Act, FDA guidance, EEOC rules — regulators now expect auditable AI records. "We didn't keep them" isn't an acceptable answer.
What changes with AI attestation
One API call after your AI generates its output. No model changes, no proxy, no middleware. Invoance records exactly what went in and what came out — permanently, cryptographically, and independently verifiable by anyone.
The exact prompt and the exact response are fingerprinted and bound to the same record. You can prove not just what the AI said, but what it was asked.
Which model, which provider, which version — all anchored as part of the signed record. When models get updated or deprecated, the attestation still points to the exact version used.
The moment of generation is cryptographically signed. It can't be backdated, adjusted, or overwritten. The timestamp is part of the proof, not metadata attached to it.
Every attestation produces a public verification link. Regulators, auditors, opposing counsel — anyone can confirm the record's integrity without an Invoance account.
Attestation runs alongside your existing pipeline. Your models, your prompts, your infrastructure — all unchanged. Invoance adds the proof layer without touching inference.
Each attestation is signed with your organization's key. The proof shows who ran the AI, what it produced, and when — all in one independently verifiable record.
How it works
Your AI pipeline stays exactly the same. Invoance sits after the generation step — it receives a copy of what happened and anchors it. No model changes, no proxy, no middleware.
Your models, your prompts, your pipeline — nothing changes. The AI produces its output through whatever system you use today.
One API call sends the prompt, response, and model metadata. Invoance fingerprints, signs, and writes the record to the immutable ledger.
The attestation is now tamper-evident and independently verifiable. Anyone with the verification link can confirm what the AI produced, unchanged.
No model changes required. Attestation is a parallel operation. Your AI pipeline continues unchanged. Invoance adds the proof layer without touching inference.
When AI decisions get questioned
AI outputs are challenged when they cause harm, deny services, or produce costly mistakes. In every case, the question is the same: can you prove what your system actually produced, unchanged, at a specific time?
An AI-assisted clinical recommendation is challenged 18 months after the patient visit.
Internal logs and screenshots are presented. Opposing expert contests chain of custody. The original AI output can't be independently verified.
Attestation record shows the exact model output, model version, and timestamp. Tamper-evident by construction. Verifiable by any third party.
A regulator audits 50,000 AI credit decisions to check for post-hoc adjustment.
Database exports are produced. The auditor requires additional attestation from the engineering team. Months of back-and-forth.
Every decision has an immutable attestation with cryptographic proof. The auditor verifies independently via public URLs.
A dispute over an AI-drafted contract clause — opposing party claims human intervention changed the output.
No mechanism to prove when the AI generated the clause versus when it was edited. The timeline is reconstructed from memory.
Attestation anchors the AI output at generation time, independent of document edit history. The signed record settles the question.
An employment discrimination claim alleges the AI hiring tool was biased in its recommendations.
Original AI outputs are reconstructed from application logs. Credibility is contested. No independent verification possible.
Original AI recommendations were cryptographically anchored before human review. The unaltered record is independently verifiable.
What attestation proves — and what it doesn't
Attestation is a technical guarantee, not a legal or factual one. What it provides — an immutable, independently verifiable record of what happened — is exactly what is absent from most AI systems today. Being precise about this distinction is what makes the proof credible.
What you pay vs. what you cover
Slide to your monthly AI volume. See exactly what attestation costs and how much unverified exposure it eliminates.
See what you pay and what you protect. Every event is anchored, timestamped, and independently verifiable — turning potential exposure into documented proof.
The regulatory landscape
Multiple regulatory frameworks now require or strongly imply that AI systems in high-stakes domains maintain auditable records. The trend is clear: if your AI influences decisions, you'll need to prove what it said.
2026 enforcementHigh-risk AI systems must maintain logs of inputs and outputs for post-market monitoring and regulatory audit.
Medical devicesSoftware as a Medical Device using AI must support transparency and traceability of model decisions.
Federal evidence rulesElectronic records are self-authenticating when generated and stored with process integrity controls.
Employment lawEmployers using AI in hiring must demonstrate the absence of discriminatory outcomes, including producing original AI outputs.
Financial regulationAI-driven credit decisions must be explainable, and the original decision preserved for adverse action review.
Security standardsInformation security frameworks increasingly expect auditability of automated decision systems as part of control environments.
Your AI is making decisions now. Start proving them.
AI attestation is available on all plans. No model changes required. One API call per output — permanent, tamper-evident, independently verifiable proof.
AI Attestation — Verifiable Proof of AI Outputs and Decisions
When your AI makes a decision — prove exactly what it said, when it said it. AI systems are making real decisions — approving loans, recommending treatments, screening candidates, drafting contracts. AI attestation creates a permanent, tamper-evident record of every AI input and output at the moment of generation. Designed for EU AI Act compliance, ISO 42001, and regulatory audits.