Now offering 10 free AQE assessments for founding users this month  →
AI Deployment Qualification

Before you deploy AI, can you prove it's ready?

One fixed-rules assessment. One qualification verdict. Same inputs, same verdict, every time.

Real verdict

"Named accountable owner confirmed. Deployment exposure and control signals are within the qualified range." QUALIFIED WITH CONDITIONS · three mandatory actions before full qualification.

Now offering 10 free this month
No sales call
Certificate in minutes
Deployment exposure × deployment control
QUALIFIED PRODUCTION READY OWNERSHIP REQUIRED DEPLOYMENT BLOCKED
QUALIFIED WITH CONDITIONS

Not a personal opinion about your AI. A fixed-rules verdict, built on twenty-plus years of governance methodology.

The credential behind AQE isn't a platform certification. It's twenty-plus years applying rules-based governance methodology across regulated sectors, built into a fixed rules engine, not a consulting judgement that shifts by reviewer.

“Trust our judgement on your AI deployment.”

  • That's a claim built on opinion, and opinions vary by reviewer.
  • Not what a fixed rules engine actually depends on.

Twenty-plus years of governance methodology, built into a fixed set of rules.

  • Applied across financial services, government and healthcare for two decades.
  • Built and tested: 526 automated tests behind the rules engine.
  • UK, US, Charity and NHS jurisdictions supported.
Same rules, same verdict, every time. Not a consulting opinion that shifts by reviewer.

Same input. Same verdict. Every time.

Ask a general AI chat tool the same readiness question twice and you can get two different answers. Different wording, different confidence, sometimes a different conclusion. AQE checks your answers against a fixed set of qualification rules, not a model writing fresh text each time. Try it below.

AQE Engine
Governance & Compliance · DEFICIENT Some evidence exists but is not structured or audit-ready. Required before qualification: complete or update the DPIA, formalise the AI policy, assign named accountability for AI governance. Qualification impact: qualification blocked.
Run 1 of 1Identical every run
A general AI chat tool
It might be worth reviewing your governance documentation before going ahead. A few gaps could be worth looking into.
Run 1 of 1Wording shifts each run

Same question, asked three different ways by a general AI chat tool. All three sound plausible. None cites a fixed rule, none is reproducible, and none would survive being handed to a board. An AQE finding is a lookup against fixed thresholds. It comes back the same, with the evidence behind it, every time.

This is what one dimension of a real certificate looks like.

Data Readiness · CONDITIONAL

Evidence: Q1–Q5, threshold for PASS is 7

  • Data assets are partially identified. Gaps in coverage will limit AI scope.
  • Mix of structured and unstructured data. Structuring effort needed for target use cases.
  • Data quality is inconsistent. Monitoring and validation required before AI deployment.

Required before full qualification: complete the data asset inventory, close the lineage gaps identified, establish routine data quality monitoring.

Qualification impact: qualification constrained.

This is not a maturity score with no explanation attached. Every finding traces back to specific answered questions against a fixed threshold, and every dimension carries its own remediation, not a generic checklist repeated five times.

5
readiness dimensions, each independently scored
24
structured questions, roughly ten minutes
1
document: Qualification Certificate plus Evidence Book

Organisational readiness, not model capability.

These aren't weighted equally by chance. Fifty-two percent of organisations cite data quality as their primary blocker to deploying agentic AI, more than governance, tooling or process combined. It's the dimension most deployments actually fail on, not one check among five.

1
Data Readiness
Single source of truth, lineage, semantic consistency across systems — the most common failure point.
2
Process Maturity
Automation candidates, decision consistency
3
Tooling & Infrastructure
Stack, integration, legacy constraints
4
People & Capability
Ownership, training, leadership mandate
5
Governance & Compliance
Policy, DPIA, named accountability
Want to check your own data readiness before you run AQE? Download the free AI Agent Data Readiness Framework — a sixteen-question self-assessment covering all four signals, no form required.

Three steps from intake to certificate.

01

Complete the assessment

Twenty-four structured questions across five dimensions, plus who's accountable and how the deployment operates. About ten minutes. No technical documentation required.

02

The engine runs

A fixed rules engine, not a model, scores each dimension and checks named-owner and governance conditions against the qualification rules. Same inputs always produce the same verdict.

03

Certificate delivered

A Qualification Certificate and supporting Evidence Book, delivered within minutes: the verdict, the reasoning, the conditions, and every scored answer behind it.

A fixed-scope qualification decision.

  • Fixed-rules verdict. Same inputs, same result, every time.
  • A Governance override rule, not just a score: a serious governance gap can block qualification outright regardless of everything else.
  • Certificate delivered within minutes. No follow-up call required.
  • Reusable before every new AI deployment you scope.

Not advice. Not a build partner.

  • We do not provide legal advice.
  • We do not build or fix the AI system for you.
  • We do not offer retainers or ongoing consulting.
  • We do not monitor a deployment once it's live. That's a different problem.
Already deployed? AQE qualifies readiness before you build. CLEARANCE picks up from there, checking what you actually shipped against named regulatory obligations once it's live.

Three ways to find out if you're ready.

CategoryAQEAsk a general AI chat toolSkip the check, build anyway
Time to resultMinutes, same dayInstant, but unverifiedNone. The gap surfaces later, at cost
ConsistencySame input produces the same verdict, every runWording and conclusions can shift between runsNo answer to compare against
Evidence trailFull Evidence Book, every question and scoreNo audit trail behind the answerNone, discovered under scrutiny instead
Governance overrideA serious governance gap blocks qualification outrightNo mechanism to catch thisFound by a regulator or the delivery team, not you
Cost if wrongOne fixed fee, shown before you payFree, but nothing to show for it if challengedA failed or reworked deployment

Before you start.

Is this legal advice?
No. AQE identifies evidence gaps against named frameworks and thresholds. It is not a determination that you are in breach of anything, and it does not replace your own legal or compliance advice.
What does "Qualified with Conditions" actually mean?
It means a named accountable owner is confirmed and the deployment's exposure and control signals sit within the qualified range, but specific conditions still need to be closed before full qualification. The certificate states exactly which ones, and why the verdict held despite them.
How is this different from asking an AI chatbot the same question?
A chatbot writes a fresh answer in free text every time you ask, and that answer can change. AQE checks your answers against fixed, version-controlled rules. The same input gives the same verdict every time. See the demo above.

Now offering 10 free qualification certificates for founding users this month.

No card required. If it's useful, we'll ask permission to feature you as a founding reference. Never a condition of taking part.

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