Trust & Controls

AI Compliance Automation That Turns Actions Into Evidence

The differentiator versus config scanners: a real Policy Decision Point returns a verdict and an Action Trust Score for every governed AI action and writes a tamper-evident ledger entry - so governance decisions become first-class compliance evidence.

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Fintra · Policy Decision Point
ACTIONS GOVERNED
1,204
today
AVG TRUST SCORE
82 / 100
band: Trusted
LEDGER
Hash-chained
tamper-evident
Agent A · export customer datahuman-review (score 41)
Agent B · post journal entryallow-with-logging (88)
Agent C · change access policyrecommend-block (23)
Agent D · read dashboardallow (95)

Illustrative product view

What makes this different from Vanta and Drata

Config scanners watch your cloud settings. Fintra additionally governs the AI agents and automations acting inside your business. For every action, a real Policy Decision Point (PDP) returns a verdict - allow, allow-with-logging, step-up, human-review, or recommend-block - attaches an Action Trust Score, and writes a tamper-evident, hash-chained entry to an evidence ledger. Governance decisions become first-class compliance evidence, not log lines you reconstruct after a finding.

VerdictMeaningTypical trigger
allowProceed, recordedRoutine action, high trust score
allow-with-loggingProceed with extra evidence capturedSensitive but expected action
step-upRequire stronger authentication firstElevated risk or unusual context
human-reviewRoute to a person before proceedingConsequential or low-confidence action
recommend-blockAdvise against; record the recommendationHigh risk or low trust score
The five verdicts the PDP can return

The Action Trust Score

Every actor carries an Action Trust Score from 0 to 100 with a trust band. The score reflects how an agent has behaved - an agent that drifts toward risky actions loses standing before it causes a finding, and its verdicts tighten accordingly. The score is explainable: you can see why any single action received the verdict it did.

  • Per-actor score (0–100) with a trust band, updated continuously as actions are decided.
  • Decision Intelligence: an auditor-grade explanation of why any action got its verdict.
  • Adaptive learn loop that is escalation-only - it can tighten a decision but never auto-loosens one.
  • Hash-chained ledger you can verify, so evidence can be shown to be untampered.

The governed-action to evidence loop

How an action becomes evidence

  1. 1

    An action is proposed

    An AI agent or automation attempts an action inside your business.

  2. 2

    The PDP decides

    The Policy Decision Point returns a verdict and an Action Trust Score with a reason.

  3. 3

    The decision is recorded

    A tamper-evident, hash-chained entry is written to the evidence ledger.

  4. 4

    It flows to controls

    The decision rolls up as evidence that the relevant control operated on the automation layer.

  5. 5

    The loop learns

    Patterns feed the adaptive learn loop, which can escalate future scrutiny - never silently relax it.

Why decisions count as evidence

Frameworks increasingly ask you to prove that automated systems operate under control - SOC 2 CC7 monitoring, NIST CSF Govern, ISO 42001 human oversight. A recorded decision with a verdict, a score, a reason, and a verifiable ledger position is exactly that proof, extended to the layer that config scanners cannot see.

Frequently asked questions

Does Fintra actually block risky AI actions in production?

By default, no. The Policy Decision Point decides and records - it returns a verdict and Action Trust Score and writes a tamper-evident ledger entry, but it does not actuate or block your production systems. The one genuine gating seam is the opt-in Fintra MCP tool-call boundary, and only when you turn it on. We describe this as a decision-and-evidence fabric, not enforcement across your cloud.

What is the Action Trust Score?

A 0–100 score with a trust band, per actor, updated as actions are decided. It reflects behavior, so a drifting agent loses standing and its verdicts tighten. It is explainable - you can see why any single action received its verdict - and the adaptive learn loop can only escalate scrutiny, never auto-loosen a decision.

Do the AI drafting and answering features work without setup?

The decisioning, scoring, and ledger work as the core loop. AI-assisted policy drafting and questionnaire answering additionally need a configured LLM provider key; without one they return labeled mock output. The governed-action-to-evidence loop also requires a configured sink before it writes.

How is this different from a cloud security posture tool?

Those tools scan cloud configuration. Fintra governs the AI agents and automations acting in your business and turns their decisions into evidence. It is complementary, not a replacement - and it does not claim live agentless cloud scanning or enforcement across cloud, identity, and SaaS.

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Turn AI actions into evidence

Decide, score, and record every governed action - honestly bounded, and audit-grade explainable.

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