Audit evidence, every day

Every gate in the AI factory writes down what it decided and why. The evidence for your next audit is collected as you run, not rebuilt the month before.

What a decision record holds

One schema for every band, so a model promotion, a held document and a refused prompt can be queried together.

FieldWhat it captures
WhoTenant, user or workload identity, and the session
WhatThe model, dataset, agent or document, by version and hash
Which gateBand, stage and the policy version that decided
DecisionAllow, hold or block, with a reason code and any scores
WhenTimestamp, and the hash of the previous record in the chain

How the record is kept

A control you claim is a control you can show, so the record has to survive scrutiny.

  • Append-only

    Records are only ever added. Nothing in the platform can edit or delete one inside its retention period.

  • Hash-chained

    Each record carries the hash of the one before it, so a gap or an edit breaks the chain and shows.

  • Retained

    Retention is set per tenant to match your obligations, 365 days by default.

  • Forwarded

    Normalised to CEF and OCSF and in your SIEM within seconds, so a copy lives outside the platform too.

What you hand an auditor

Each artifact, what it contains, and examples of the clauses it supports.

ArtifactContentsSupports
Decision recordsEvery gate decision, append-only and hash-chainedISO/IEC 27001 A.8.15; EU AI Act Art. 12; NIST AI RMF Manage
ML-BOMs and attestationsBill of materials per model, with scan results as in-toto attestationsISO/IEC 42001 A.10; ISO/IEC 27001 A.5.21; OWASP LLM03
SignaturesSigstore signatures on models and datasets, logged to a transparency logISO/IEC 27001 A.8.24; OWASP LLM03 and LLM04
Policy historyEvery policy as code, versioned and reviewedISO/IEC 42001 A.2; NIST AI RMF Govern
Red-team reportsFindings by attack class and severity, run after runEU AI Act Art. 15; NIST AI RMF Measure; ISO/IEC 23894
Data handling recordsPII actions per batch, provenance per chunk, key usagePDPL regimes; ISO/IEC 27001 A.8.11; EU AI Act Art. 10
Incident casesAI events worked in your SOC, with playbook and outcomeISO/IEC 27001 A.5.24 to A.5.28; NIST AI RMF Manage

An audit, step by step

The same four moves, whichever framework the auditor is testing against.

  1. 1

    Scope the systems

    Export the inventory: every model, dataset, agent, skill and MCP server, with owner, version and approval.

  2. 2

    Show the controls

    Export the policy history: which rule applied at which gate, when it changed and who approved the change.

  3. 3

    Prove they ran

    Query the decision record for the audit period and verify the chain end to end.

  4. 4

    Show the exceptions

    Pull the blocks, holds, red-team findings and incident cases, with how each was resolved.

Bring your whole AI factory. We'll secure it.

Put the gate in front of every model, dataset, prompt and agent, on the infrastructure you already run, and keep the record that proves it held.

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