// Free AI Readiness Assessment

Is your AI ready for
regulated deployment?

Answer 14 plain-language questions about your AI tool, device class, and regulatory status. Get a compliance readiness score, gap analysis, and recommended evaluation tier — free, in under 5 minutes.

⏱ Under 5 minutes 🔒 No signup required 📋 Instant results 🏥 Medical device focused

// Step 01 of 04

Tell us about your device

We need to understand what your AI tool does and how it is classified — this determines which regulatory frameworks apply.

What does your AI tool do? *

Brief description — e.g. "analyzes X-ray images to detect lung nodules" or "automates prior authorization decisions"

What is your device regulatory classification? *

Select the highest applicable classification

How is your AI software deployed? *

What is your IEC 62304 software safety classification?

Class A = no injury possible · Class B = non-serious injury possible · Class C = serious injury or death possible

* Required fields

// Step 02 of 04

Tell us about your AI

The type of AI model you use determines which evaluation frameworks apply and how complex the assessment will be.

What type of AI model does your device use? *

Does your AI use a third-party foundation model or API? *

Examples: Claude API, OpenAI GPT-4, Google Gemini, AWS Bedrock, Azure OpenAI, Hugging Face models

How does your AI model change or update after deployment? *

How is your AI device connected?

// Step 03 of 04

Your regulatory status

Tell us where you are in the regulatory process — this determines the urgency of your compliance gaps.

Which markets are you targeting? *

Select all that apply

What is your current regulatory submission status? *

Are you aware of your EU AI Act obligations?

The EU AI Act has two key deadlines: December 2, 2027 (Annex III high-risk AI) and August 2, 2028 (Annex I product-linked AI)

// Step 04 of 04

Your compliance readiness

Final questions about your current documentation and validation status — these directly determine your readiness score.

Has your AI been tested against specific regulatory frameworks? *

Has your AI been tested for demographic bias? *

FDA and CMS require equal performance across age, sex, race, and geography

Do you have an independent third-party assessment of your AI? *

Internal testing alone does not satisfy hospital legal teams or regulatory bodies

Do you have a post-deployment monitoring plan for your AI?

FDA PCCP Final Guidance (August 2025) requires a Predetermined Change Control Plan for AI medical devices

// Your Assessment Results

Your AI Compliance
Readiness Score

// Enter your work email to see your full results

// No spam. Your results are confidential. We will email you a copy.

// ClearanceAI Readiness Assessment ACTION REQUIRED

/ 100

Compliance Readiness Score

✗ Not Ready — Critical Gaps

Regulatory Alignment

Bias & Fairness

Independent Evidence

Post-Deploy Monitoring

AI Architecture Risk

// Key Findings

🚨

Critical — No validation documentation — No validation documentation exists. This is a critical gap for any regulated market deployment.

⚠️

No post-deployment monitoring yet — PCCP is required for FDA AI medical devices. Planning to build it after deployment is too late for submission.

⚠️

Third-party foundation model (SOUP) — Your AI uses a third-party model treated as Software of Unknown Provenance (SOUP) under IEC 62304. This requires additional governance documentation including anomaly lists, version pinning, and impact analysis.

// Regulatory Clause Gap Analysis

Critical Gap

Moderate Gap

Requirement Met

Critical
Gaps

Moderate
Gaps

Requirements
Met

Total Clauses
Examined

Framework	Clause / Section	Requirement	Your Status	Gap Severity
ISO 14971:2019	§ 7.1	Post-production information — systematic collection and review of field performance data	⚠ Not formally established	🟡 Moderate
FDA 2025 AI Guidance (Draft)	§ 5.1	AI/ML model documentation — intended use, model architecture, and training approach	✓ Documented	🟢 Met
FDA 2025 AI Guidance (Draft)	§ 5.3	Demographic subgroup performance data — age, sex, race, and geography	✓ Documented	🟢 Met
FDA 2025 AI Guidance (Draft)	§ 5.4	Training data transparency — dataset composition, provenance, and bias examination	✓ Documented	🟢 Met
FDA 2025 AI Guidance (Draft)	§ 7.1	Independent third-party verification or validation evidence	✗ None	🔴 Critical
FDA PCCP Final Guidance	§ 4.1	Predetermined Change Control Plan — documented and FDA-aligned	✗ No PCCP	🔴 Critical
FDA PCCP Final Guidance	§ 4.2	Defined drift thresholds with documented clinical justification	✗ Not defined	🔴 Critical
FDA PCCP Final Guidance	§ 4.3	Revalidation trigger — conditions requiring full revalidation after model change	✗ Not defined	🔴 Critical
NIST AI RMF	GOVERN 1.1	AI risk governance policy — organizational accountability for AI risk	✓ Established	🟢 Met
NIST AI RMF	MAP 5.1	AI system risk identification — documented hazards and failure modes	✓ Documented	🟢 Met
NIST AI RMF	MEASURE 2.5	Bias testing — subgroup performance evaluation and documentation	✓ Completed	🟢 Met
NIST AI RMF	MANAGE 4.1	Post-deployment monitoring — ongoing performance oversight program	✗ Not established	🔴 Critical
ISO 42001:2023	Clause 6.1	AI risk assessment — systematic identification and treatment of AI-specific risks	✓ Completed	🟢 Met
ISO 42001:2023	Clause 8.4	AI system performance evaluation — documented testing against objectives	✓ Documented	🟢 Met
IEC 62304:2006	§ 8.1	SOUP identification — third-party AI components documented as Software of Unknown Provenance	✗ Not documented as SOUP	🔴 Critical
IEC 62304:2006	§ 8.1.2	SOUP anomaly list — known anomalies and version pinning documented	✗ Not established	🔴 Critical
ISO 14971:2019	§ 4.4	Hazard identification — AI-specific failure modes including hallucination and drift	✓ Identified	🟢 Met
EU AI Act	Article 9	Risk management system — documented AI lifecycle risk management	✓ Established	🟢 Met
EU AI Act	Article 10	Data governance — training data bias examination for health outcomes	✓ Documented	🟢 Met
EU AI Act	Article 14	Human oversight — defined mechanisms for human review and override of AI outputs	✓ Defined	🟢 Met
CMS Requirements	Non-Discrimination	Equal AI performance across all patient demographic groups — documented parity	✓ Documented	🟢 Met

// This gap analysis is based on your self-reported compliance status. A ClearanceAI Layer 1 or Layer 2 evaluation will verify each clause against your actual AI model documentation and produce a formally auditable gap report.

// Recommended Next Step

Recommended: Start with Layer 1 — Automated Evaluation ($3,500 one-time or $1,500/month)

Critical compliance gaps were identified that must be resolved before deployment. We strongly recommend starting with a ClearanceAI Layer 1 Evaluation — our automated evaluation engine will give you a complete gap analysis and remediation roadmap so you can address issues systematically. Investing in a Layer 2 formal assessment before resolving these gaps would be premature. Layer 1 is your starting point.

// Layer 1 one-time: $3,500 · Monthly subscription: $1,500/month · Path to Layer 2 Comprehensive ($25,000) after remediation

// YOUR PATH TO READINESS
Layer 0 Free Assessment (done) → Layer 1 Automated Evaluation ($3,500) → Layer 2 Comprehensive ($25,000)

Request Free Evaluation → View Sample Report

// NEXT STEP

Layer 1 Evaluation — Essential Next Step

Your assessment identified critical compliance gaps that need immediate attention. A ClearanceAI Layer 1 independent evaluation maps every gap to named regulatory clauses and delivers a formal remediation roadmap before your next FDA submission or Notified Body audit.

// HOW WE HANDLE YOUR DOCUMENTS

→Zero retention — all submitted documents are permanently deleted within 30 days of report delivery

→No training — your documents are never used to train any AI model

→NDA required — a mutual Non-Disclosure Agreement is signed before any document is submitted

→No sharing — your documents and results are never shared with any third party

→SHA-256 anchored — your final report is cryptographically timestamped and tamper-evident

Your evaluation results are 100% private. You control what is shared and with whom.

// DOCUMENTS REQUIRED FOR YOUR LAYER 1 EVALUATION

Based on your assessment responses

AI Risk Assessment

Required — evaluates ISO 42001 Clause 6.1 and EU AI Act Article 9

Performance Validation Report

Required — evaluates ISO 42001 Clause 8.4 and NIST MEASURE 2.5

PCCP Document

Required for FDA — evaluates FDA PCCP Final Guidance § 4.1, § 4.2, § 4.3

Training Data Documentation

Required for FDA — evaluates FDA 2025 AI Guidance § 5.3 and § 5.4

SOUP Identification Document

Required — third-party AI component identified — evaluates IEC 62304 § 8.1

Third-Party Model Documentation

Vendor documentation for the third-party AI component

ISO 14971 Risk Management File RECOMMENDED

Recommended — evaluates AI-specific hazard identification against ISO 14971 § 4.4

// REQUEST LAYER 1 EVALUATION

Complete the form below and we will be in touch within 1 business day to discuss your evaluation and send over the NDA for your review.

FULL NAME *

COMPANY NAME *

EMAIL ADDRESS *

DEVICE / AI TOOL TYPE

BRIEF MESSAGE (OPTIONAL)

NDA sent within 1 business day · Results 100% private