Turn AI regulation into
executable compliance.
PEARL translates fragmented HKMA, SFC, PCPD, and IA requirements into tailored control baselines, supervisory audit dossiers, and continuous evidence packs — so regulated institutions can deploy AI with absolute defensibility.
Deterministic Control Compilation • Zero LLM Hallucinations • Audit-Ready from Day 1
Trusted by Risk & Compliance Teams at
The Translation Gap in Regulated AI.
Regulation is drafted in legal prose, but financial institutions must operationalize it as precise engineering controls.
Compliance vs. Engineering
2LoD Compliance understands regulatory obligations but lacks technical architecture blueprints. Engineering understands models but cannot map legal circulars. The outcome: risk paralysis and multi-month delays.
Slow & Static Consulting
Traditional advisory firms require 6+ months and hundreds of thousands in billables to produce a point-in-time narrative report. The moment model hyperparameters or prompts drift, the audit baseline becomes obsolete.
Empty GRC Platform Shells
Generic GRC tools offer workflow trackers but contain zero domain-specific AI logic for Hong Kong regulatory frameworks. They leave institutions asking: "Given our specific license and model topology, what exact controls must we deploy?"
The AI Compliance Knowledge Matrix.
The continuously verified regulatory ontology that powers PEARL's deterministic mapping engine.
Deterministic Precision
PEARL's core technological moat: an automated regulatory knowledge graph. We algorithmically parse global AI mandates (HKMA, SFC, EU AI Act, MAS) into structured, verifiable engineering control nodes with paragraph-level provenance.
Hallucination-Free Engineering
Unlike generative AI which invents citations, PEARL executes deterministic graph evaluation. Every triggered control links directly to verbatim regulatory clauses, creating an unassailable audit defense.
Transforming Ambiguity into Action.
Given your institution's license profile and AI system topology, exactly what technical and governance controls are mandatory?
01 / Input: DNA
- ▪ SFC Type 1, 4, 7 & 9 Licensed Corps
- ▪ HKMA Authorized Institutions (Banks)
- ▪ Authorized Insurers & MPF Trustees
02 / Input: Domain
- ▪ Algorithmic Trading & Smart Order Routers
- ▪ Robo-Advisory & Automated WealthTech
- ▪ Customer GenAI & Autonomous Credit Scoring
03 / Output: Control Baseline
Cross-regulatory core: Bias testing, Model explainability, Human-in-the-loop oversight.
Jurisdiction-specific conduct rules routed by SFC/HKMA supervisory policies.
— HKMA Supervisory Policy Manual (SPM TM-E-1)
See the Platform in Action.
A single pane of glass bridging policy intent and CI/CD reality.
Enterprise Model Inventory (MRM Registry)
Atlassian Jira DevSecOps Sync
Compiled Defense Dossiers
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Defense Dossier Generation.
Dual-track institutional deliverables: Executive Audit Dossiers for Board/Regulators + DevSecOps Jira matrices for Engineering.
Once your profile is compiled, PEARL produces an implementation-ready Defense Dossier customized to your regulatory licenses and AI technical stack.
Stop building governance from scratch. Arm your 2LoD Risk Committee with formal audit packs and your DevOps team with policy-as-code control tickets.
Continuous Governance & Audit Lineage.
From point-in-time compliance assessment to ongoing model lifecycle assurance.
Real-Time Regulatory Delta.
Every new circular issued by HKMA or SFC triggers an instantaneous recalculation against your active control baseline. Automatically identify coverage gaps before regulatory inquiries arrive.
Model Version Lineage.
PEARL tracks control diffs across AI model iterations, generating an immutable audit trail for internal Model Risk Committees and external regulatory inspectors.
Supervisory Attestation.
Every baseline deliverable carries a SHA-256 integrity checksum. When HKMA or SFC conducts an on-site supervisory review, you possess mathematical proof of governance compliance.
Traditional Consulting vs. PEARL Trust OS.
Why manual advisory engagements fail the speed of production AI development.
Built by Architects Who Defended Institutional Audits.
Founder Ming Liu served as Business Information Security Officer (BISO) at Fidelity International and as a Senior Consultant at Deloitte. He understands institutional risk review because he chaired those committees.
"I built the exact deterministic control framework I would have required during my time as a 2LoD risk gatekeeper."
— Ming Liu, CISSP / CISM / CISA
From Regulatory Ambiguity to
Deterministic Governance.
The AI compliance infrastructure that makes rapid, defensible AI deployment possible for regulated financial institutions.