BYOK via External HSM
100% of use casesCustomer-controlled key sovereignty; cascaded encryption independent of the cloud provider.
- practice-derived3 triggering use cases require BYOK via External HSM
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 →
Customer due diligence, perpetual monitoring and AMLA supervisory expectations for AI-driven KYC/AML systems.
Customer-controlled key sovereignty; cascaded encryption independent of the cloud provider.
AMD SEV / Intel TDX: data protected from the cloud operator even in memory during inference.
Per-client storage boundary for raw payloads, intermediate artefacts and outputs, so no tenant data is co-mingled or reachable across engagements.
DORA-grade continuity: regional redundancy, chaos testing, exit strategies for critical third parties.
Hierarchical trace spans for every sub-task, prompt, retrieved document and API call — the reconstructible decision path for Art. 12/14 and PLD disclosure.
Governed runtime workspace operationalizing Art. 10: traceable lineage for every RAG chunk and training record at execution time, canonical version-controlled business glossary (documents Art. 10(2)(d) baseline assumptions), and continuous data-quality monitoring with threshold alerts and logged remediation for the Art. 10(3) 'error-free and complete' standard.
Scoring model: jurisdiction (CLOUD Act exposure), zero-data-retention, BYOK support, audit evidence (C5/AIC4/ISO 42001/EN 18286:2026), tenant isolation.
Authenticated, policy-checked entry point for client payloads; enforces tenant identity, schema validation and rate limits before any data reaches an inference path.
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.
Per-agent identities, short-lived scoped tokens, OBO flow enforcement — the identity substrate of agentic zero trust.
Representativeness checks, bias metrics and mitigation per ISO/IEC 5259; versioned datasets with lineage.
Agents never hold target-system keys; the gateway injects centrally managed credentials after policy checks.
Computes a probabilistic confidence score for every output and holds the transaction when the score falls below the workflow's regulatory threshold.
Policy-as-code decision point (PDP) with enforcement points (PEP) in front of every tool call: versioned policies in Git, microsecond evaluation, typed action schemas — authorization decided outside the model's reasoning space, never in the prompt.
OCR, layout parsing and semantic clause extraction over filings, contracts and invoices, emitting structured records with span-level source references.
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.
Beneficial-ownership resolution, sanctions/PEP list matching and alert scoring with tunable thresholds and full match-evidence capture.
Operator stop controls and degraded-mode fallbacks; real-time override (veto) channels for HOTL operation.
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.
Automated detection, pseudonymisation and blocking of personal data in inputs, retrievals and outputs.
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.
Cost/iteration caps, loop detection, anomaly-triggered mandatory approval (CodeBuddy 'suspicious command override').