Regulated AI Navigator
Turn an AI use case into its EU AI Act risk class, the regulations it triggers, the obligations, the architecture and the evidence you owe — in about two minutes.
Community-curated knowledge graph, peer-reviewed by experts across law, engineering and governance. Every change traceable →
Every regulation in the graph resolves into concrete technical components — through an article obligation, a control objective, a design pattern or an evidence artefact that a component must produce. Pick a regulation to see its technical surface, how each component is derived, and in which of the triggering use cases it is actually part of the required stack. The gap counts show where the graph reaches a component that no use case yet requires — those are open contribution targets, not settled answers. Open the full graph →
Primary and secondary use of electronic health data; access via health-data access bodies for AI training.
Representativeness checks, bias metrics and mitigation per ISO/IEC 5259; versioned datasets with lineage.
Computes a probabilistic confidence score for every output and holds the transaction when the score falls below the workflow's regulatory threshold.
Feature attributions for classical ML, reasoning-trace summaries for GenAI — feeds the human reviewer and the technical file.
HITL escalation queue & review UI ('Human-as-a-Tool': the agent calls the human like any other tool via propose-action objects). Confidence- and risk-threshold routing, SLA timers, structured accept/modify/reject verdicts with digital reviewer signature at gate release — each verdict is itself Art. 14 evidence and feeds the active-learning loop.
Operator stop controls and degraded-mode fallbacks; real-time override (veto) channels for HOTL operation.
Escalation triggers built from two independent signals, because raw model confidence is uncalibrated: calibrated trust scores (prompt relevance, similarity to historic successes, cross-model consistency) plus deterministic risk scores (sensitive categories, transaction value, protected data) — either crossing its threshold forces human review.
Append-only, hash-chained audit vault (WORM object-lock storage, AES-256 at rest, TLS 1.3 in transit). Guarantees tamper-evidence within the organization's trust domain — which stops your own team, but not an admin who can rebuild the vault. Pair with an external trust anchor and key ceremonies outside the operating team for evidence that holds against the insider scenario.
Automated detection, pseudonymisation and blocking of personal data in inputs, retrievals and outputs.
Pre-model validation of user input: injection detection, topic blocking, encoding checks.
Continuous evaluation against golden sets and sampled human verdicts; raises drift alerts and feeds the recertification cycle.
Abstraction layer decoupling application logic from model providers: dynamic routing on capability, cost, latency SLA and regulatory constraint (sensitive-data classes pinned to ZDR private/VPC endpoints or on-prem open-weight instances); real-time health monitoring with automatic fallback to secondary endpoints or local fine-tuned models on outage/latency spikes. Discharges resilience duties (DORA-class), prevents provider lock-in, and makes model deprecations a routing-table change instead of a re-architecture. Router decisions are logged into the decision trace — model version per event is an audit-packet field.
Faithfulness scoring of answers against retrieved sources; deterministic fallback instead of hallucination; schema-validated structured output.
Relevance, freshness and per-user permission checks on every retrieved chunk; curated, versioned index.
Synthetic-content labelling & watermarking: visible disclosure plus machine-readable provenance (C2PA Content Credentials) embedded in generated images, audio and video; metadata identifying artificial origin survives common transformations. Discharges Art. 50(2)/(4) for deepfakes and synthetic media; verification telemetry (watermark presence/validity checks at publication gates) is the corresponding evidence stream.