RegTECH & SupTECH

Transform Compliance from
Cost Centre to Constitutional Capability

The world's first hardware-accelerated RegTech platform delivering mathematically provable, continuous compliance – where governance is engineered as an intrinsic, continuously verifiable runtime property.

EU AI ActEU AI Act DORADORA NIS2NIS2 GDPR Art. 5GDPR Art. 5 ISO 42001ISO 42001
Architecture

The Constitutional Stack

Seven integrated layers transform compliance from reactive auditing into continuous, provable enforcement – backed by hardware acceleration and neuro-symbolic reasoning.

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Constitutional Stack for RegTECH/SupTECH – layer by layer

What: Vertical stack: (bottom) silicon attestation (HBOM) → (next) OS + secure boot → (next) Axiom MESH (constitutional kernel) → (next) Agreement DAGs (per-tenant compliance regimes) → (next) Stanzas/Runbooks (executable controls) → (top) the regulator's window (live MVEB feed, Submission Tokens, recomputable audit). Each layer annotated with the framework it satisfies (DORA, NIS2, EU AI Act, MiCA).

Why: RegTECH buyers (CCOs, regulators) read stacks. This is the single image that lets them map their compliance obligations to platform layers.

Layer 7

Human Interface & Regulatory Reporting

Auditor dashboards, regulatory reporting APIs, explainable-AI decision trails, and supervisor-grade evidence packages.

Neuro-symbolic AI that interprets intent, verifies against Agreement DAGs and Axiom MESH, and generates real-time compliance verdicts.

Layer 5

DRAGONDRAGON Engine

DAG Reasoning Adjudicator of Governed Ontologies & Nodes – three adjudication passes: Syntactic (eBPF/eBPF wire-speed), Semantic (GPU graph reasoning), Pragmatic (TEE-based consent and jurisdiction evaluation).

Governed execution engine translating Agreement DAGs into real-time verifiable actions, with adjudication gates at every critical step.

Agreement DAGs as machine-executable legal contracts. Axiom MESH for deontic logic. Constitutional separation of policy authorship from technical execution.

Immutable ledger of Minimum Viable Evidence Bundles (MVEBs). Hardware BOM attestation. Cryptographically signed audit trails for every governed action.

Layer 1

Hardware-Accelerated Trust Fabric (TRS-MS)

NIST NGAC graph relations bound directly to eBPF/XDP hooks on SmartNIC DPUs, multi-tenant Confidential Computing (TEE Hardware-Isolated Enclaves), cryptographic ASICs, and edge TPU appliances – active zero-trust hardware foundation.

Core Engine

DRAGONDRAGON: Multi-Modal Computational Jurisprudence

DAG Reasoning Adjudicator of Governed Ontologies & Nodes – the world's first purpose-built hardware-accelerated compliance adjudication engine.

Wire-Speed Syntactic Pass

Wire-Speed Syntactic Pass

eBPF kernel maps and software-defined validation for sub-millisecond schema and format validation – compliance at line rate.

Graph-Native Semantic Pass

Graph-Native Semantic Pass

Graph Processing Units with 3D Ultra High Bandwidth memory for ontology traversal and identity graph queries at scale.

Context-Aware Pragmatic Pass

Context-Aware Pragmatic Pass

Trusted Execution Environments (TEE) evaluate consent freshness, jurisdictional context, and real-time policy state at transaction time.

Hybrid Reasoning Fabric

Hybrid Reasoning Fabric

Orchestrates description logic, deontic logic, and probabilistic engines – combining symbolic precision with AI adaptability.

Adversarial TTP Mitigation

Adversarial TTP Mitigation

Canonicalization, grammar-aware validation, and parser hardening at ingress – defeating prompt injection and payload attacks.

Continuous Cryptographic Assurance

Continuous Cryptographic Assurance

Every adjudication produces signed, immutable attestations logged to the SoR – compliance proof as primary operational output.

Ready to Prove Your Compliance?

Start with a Discovery & Positioning Workshop to map the Salient Innovation Sets relevant to YOUR objectives, domain and sector (€2,500*), resulting in a "high-level" Report and Slide Presentation. This presents a review of strategic opportunities and cohort fit at a Contextual and Conceptual level before committing limited resources and time further.