Input Rails / Prompt Shields
100% of use casesPre-model validation of user input: injection detection, topic blocking, encoding checks.
- practice-derived2 triggering use cases require Input Rails / Prompt Shields
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 →
Intermediary services: recommender-system transparency, risk assessments for very large platforms.
Pre-model validation of user input: injection detection, topic blocking, encoding checks.
Faithfulness scoring of answers against retrieved sources; deterministic fallback instead of hallucination; schema-validated structured output.
Automated detection, pseudonymisation and blocking of personal data in inputs, retrievals and outputs.
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.