EU AI Act GPAI Compliance & Enforcement Intelligence
Pricing
from $10.50 / 1,000 results
EU AI Act GPAI Compliance & Enforcement Intelligence
Use this Actor to analyze eu ai act gpai compliance and enforcement and return decision-ready structured signals. Track EU AI Act and GPAI obligations, enforcement signals and implementation changes, then rank compliance impact, deadlines and escalation priorities.
Pricing
from $10.50 / 1,000 results
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0.0
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Developer
Rafael Barreto Haddad
Maintained by CommunityActor stats
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4 hours ago
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Use this Actor to analyze eu ai act gpai compliance and enforcement and return decision-ready structured signals. It is designed for repeatable human, API, Apify AI, and MCP-driven workflows.
Track EU AI Act and GPAI obligations, enforcement signals and implementation changes, then rank compliance impact, deadlines and escalation priorities.
Why use this Actor
AI providers and deployers need a recurring way to convert EU AI Act and GPAI regulatory updates into concrete obligation, deadline and enforcement-risk priorities. This Actor sits above raw extraction: supply a current dataset, optionally add a previous snapshot, and receive an aggregated report built for recurring monitoring and AI-agent workflows.
Key features
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Separates GPAI, high-risk, transparency and enforcement signals into decision-ready obligations.
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Compares regulatory snapshots to identify newly effective or materially changed duties.
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Ranks compliance actions by deadline and enforcement impact for recurring governance.
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Reads inline JSON rows or Apify Dataset IDs with limited READ permission.
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Writes one auditable report to the default Dataset and
INTELLIGENCE_REPORT.
Input
Provide currentItems directly or select an Apify Dataset with currentDatasetId. For change intelligence, add the prior period with previousItems or previousDatasetId. maxItems caps dataset loading. Optional Gen2 fields can provide a previous analysis and user-supplied economic assumptions.
Output
The Actor writes one decision-ready report to the default Dataset and to INTELLIGENCE_REPORT in the key-value store. The report includes counts, ranked signals, baseline evidence, confidence, regression state, an executive decision, recommended action, and the domain-specific portfolio score.
Example
Use the prefilled example or replace currentItems with rows from an upstream Actor. On recurring runs, provide the prior period in previousItems or previousDatasetId. The Actor normalizes common aliases, compares snapshots, ranks the strongest entity changes and emits agentAction.
Use cases
- AI governance.
- GPAI provider compliance.
- legal and policy monitoring.
- enterprise AI risk management.
Pricing
One primary pay-per-event outcome: one decision-ready intelligence report. Base price USD 0.015 before Apify tier discounts. The 256 MB data-first architecture is designed for strong unit economics.
Limitations
- Analyzes supplied public or appropriately licensed data and does not bypass restricted sources.
- Scores are decision-support signals, not predictions or guarantees.
- Keep stable identifiers across snapshots for best change detection.
- Competitor evidence is refreshed before publication because the Store changes continuously.
Workflow
upstream dataset -> current snapshot -> optional previous snapshot -> normalization -> entity aggregation -> change scoring -> ranked signals -> agentAction.