The compliance infrastructure
advanced AI requires.
OnTargetCompliance is a six-layer assurance platform — from AI system registry to regulator-ready evidence export. Every layer is connected. Every output is signed. Every claim is verifiable.
FrontierAI Registry
+ Assurance Fabric
The FrontierAI Registry is the authoritative record of every AI system in your organisation. It captures model identity, version lineage, deployment context, risk classification, and responsible ownership — the single source of truth from which all compliance activity flows.
The Assurance Fabric is the six-layer compliance infrastructure that sits above the Registry. It connects evidence collection, node-based verification, policy alignment, human oversight, and regulator export into a single, auditable workflow — for every AI system, across every applicable framework.
Together, they replace scattered spreadsheets, manual audit preparation, and one-off compliance projects with a continuous, verifiable system of record — one that produces evidence regulators accept and customers trust.
Register your first AI system in under 30 minutes.
FrontierAI Registry is designed for immediate deployment. Book a demo to see how quickly your AI inventory can be structured and documented.
Six-layer compliance stack
Each layer has a distinct function. Together they form a complete, connected assurance infrastructure — from first registration to final regulator submission.
The authoritative record of every AI system in your organisation. Each system entry captures model identity, version lineage, deployment context, intended use, risk classification, and responsible owner. The Registry is the foundation — nothing enters the compliance lifecycle without a Registry entry.
Six layers. One continuous compliance workflow.
From Registry to Export, every layer produces evidence that feeds the next. Book a demo to walk through the full architecture with a compliance specialist.
From intake to regulator submission
The Assurance Fabric manages a seven-stage lifecycle for every AI system. Each stage produces signed evidence. Each gate requires explicit sign-off. Nothing advances without a complete, verifiable record.
Intake
Register the AI system in the FrontierAI Registry. Capture system identity, model card, deployment context, intended use, and initial risk classification. Assign a responsible owner and compliance lead.
Build Provenance
Document the full provenance of the AI system — training data sources, dataset inventory, preprocessing steps, model architecture, and version lineage. Execute the Dataset Inventory Node and Model Registration Node.
Evaluate
Execute the Benchmark Execution Node. Run capability evaluations, safety benchmarks, bias assessments, and performance tests. All results are captured as signed evidence artifacts with full methodology documentation.
Safety Case
Build the structured safety case. Execute the Safety Mitigation Node — document identified risks, implemented mitigations, residual risk assessment, and human oversight mechanisms. Assign for independent technical review.
Release Gate
Execute the Independent Review Node. An independent reviewer assesses the safety case, benchmark results, and compliance documentation. The Policy Engine validates framework alignment. Executive sign-off completes the gate.
Monitor
Post-deployment monitoring captures operational performance, incident reports, and drift indicators. The Registry entry is updated with monitoring data. Triggers are configured to initiate re-evaluation if thresholds are breached.
Submit / Disclose
Execute the Submission Packet Node. Generate the regulator-ready evidence bundle, board summary, and customer assurance export. Submit to the EU AI Act database, provide customer Trust Portal access, and file with relevant regulators.
From intake to regulator submission — automated.
The 7-stage lifecycle workflow ensures no compliance step is missed. See a live run-through of an AI system moving from intake to signed evidence package.
Framework alignment, automated
The Policy Engine evaluates each AI system against the specific obligations of every applicable framework. Based on risk tier, deployment jurisdiction, and use case, it generates a compliance gap analysis and routes the system to the appropriate node workflows.
For each AI system, the Policy Engine produces a compliance obligation map — a structured list of every applicable article, control, and requirement, with current status (met / gap / not applicable), evidence references, and the node workflows required to close any gaps. The obligation map is updated automatically as the system progresses through the lifecycle.
Policy Engine maps every control to the right framework.
EU AI Act, GDPR, UK GDPR, SOC 2, ISO 27001, and Clarity Act — the Policy Engine automatically maps your AI system's evidence to the applicable framework requirements.
Structured for audit, built for scale
The platform data model is designed for compliance integrity — every entity is uniquely identified, every relationship is explicit, and every record carries a complete provenance chain.
Structured evidence from day one.
The FrontierAI data model is designed for regulatory requirements — not retrofitted. Every field maps to a specific obligation under EU AI Act, GDPR, or SOC 2.
How trust is verified, not claimed
Every compliance output in OnTargetCompliance is backed by a cryptographically signed evidence chain. The Trust Verification Envelope is the mechanism — a structured record that makes every claim independently verifiable.
Input Capture
All inputs to a node are captured and hashed before execution. The input hash is included in the Trust Verification Envelope.
Process Execution
The node executes its defined workflow in a controlled environment. Every step is logged with timestamp, actor, and outcome.
Output Signing
On completion, the node output is cryptographically signed. The signature binds the output to inputs, process log, reviewer identity, and timestamp.
Envelope Assembly
The Trust Verification Envelope is assembled: input hash, process log, signed output, reviewer identity, timestamp, and chain-of-custody reference.
Chain Verification
Any regulator, auditor, or customer with access can verify the chain — confirming every compliance claim is backed by a signed, tamper-evident evidence trail.
See the platform in action
for your AI systems.
Book a technical demo to walk through the FrontierAI Registry, Assurance Fabric, and Trust-Verified Nodes for your specific AI deployment context and regulatory obligations.