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EU AI Act Risk Classifier
x402
EU AI Act Risk Classifier is a paid API for AI agents from api.strale.io, paid per call via x402, $0.216001/call, status unknown (last checked 2026-09-15).
Classifies an AI system's risk level under the EU AI Act using rule-based analysis against Annex III, Article 5, Article 6, and Article 50 criteria
Price / call$0.216001
Success—
StatusUnknown
How this service works
Classify an AI system's risk level under the EU AI Act. Rule-based analysis against Annex III and Article 5/6/50 criteria.
Output
Returns a structured risk classification indicating the AI system's risk level (e.g. unacceptable, high-risk, limited-risk, minimal-risk) under the EU AI Act, with references to the specific Annex III categories or Article 5/6/50 criteria that triggered the classification.
Example use cases
Example prompt
“Can you classify this AI system under the EU AI Act and tell me its risk level? It's a CV screening tool that automatically filters job applicants based on predicted performance scores.”
Technical details
Endpoint
GEThttps://api.strale.io/x402/eu-ai-act-classifyWhen to prefer
Use this endpoint when you need a fast, rule-based EU AI Act compliance check for an AI system description without engaging a human legal expert. Ideal for initial triage, developer compliance checks, or automated regulatory screening pipelines. Prefer this over general LLM reasoning when you need structured, citation-backed output tied to specific EU AI Act articles and annexes.
Side effects
- Missing or empty description query parameter returns validation error
- Vague description may yield ambiguous or low-confidence classification
- Service unavailable returns HTTP 402 or 5xx error
- Description too short to match against regulatory criteria may return minimal-risk by default
Input
{
"description": "A machine learning model that analyzes medical imaging scans to detect early-stage tumors in radiological images. The system processes patient data and provides diagnostic recommendations to radiologists as a decision-support tool."
}Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object |
Output
{
"_meta": {
"payment": {
"method": "x402",
"price_usd": 0.21600000000000003,
"settlement_id": "0x7d7c98bb88eb65981866dfc0afd60820d379ea49536d318d94493a1f87c9138c"
},
"capability": "eu-ai-act-classify",
"latency_ms": 1,
"provenance": {
"source": "algorithmic",
"fetched_at": "2026-06-16T01:24:34.816Z"
}
},
"timeline": "No mandatory compliance deadline, but voluntary codes of conduct may apply.",
"prohibited": false,
"risk_level": "minimal",
"obligations": [
"No mandatory obligations under the EU AI Act.",
"Voluntary codes of conduct encouraged (Article 95)."
],
"recommendations": [
"Although not legally required, consider adopting voluntary codes of conduct (Article 95).",
"Maintain good AI development practices (transparency, fairness, safety).",
"Monitor regulatory developments — classification may change with delegated acts.",
"Document your AI system's purpose and functionality for potential future audits."
],
"matched_keywords": [],
"applicable_articles": [
"Article 95 (Codes of conduct for minimal-risk AI)"
],
"classification_reason": "No high-risk, limited-risk, or prohibited keywords detected. System appears to fall under minimal risk.",
"system_description_summary": "A machine learning model that analyzes medical imaging scans to detect early-stage tumors in radiological images. The system processes patient data and provides diagnostic recommendations to radiologi",
"conformity_assessment_needed": false
}Tags
x402
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