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Research

AML governance demonstrated across multiple domains. Each analysis uses the same deterministic engine to detect contradictions between legislation and operational outcomes.

AML Governance Principles

These analyses demonstrate OS Infinity's core capabilities:

  • Rules defined mathematically, not in natural language
  • Deterministic execution — same data produces identical results
  • Full audit trail with timestamps for every decision
  • Domain-agnostic — same engine across any domain
  • Language-agnostic — AML translates to target implementation language
  • Analysis completed in hours, not weeks

Published Studies

FAMILY LAW • 1 MARCH 2026 • 4 HOURS

Child Maintenance Service Analysis

AML governance detected 3 contradictions in CMS operations: fee revenue structure, mandatory reconsideration outcomes, and collect & pay trends relative to stated policy.

Cases Analyzed 780,600
Contradictions 3
Duration 4 hours
CROSS-DOMAIN • 1 MARCH 2026 • 2 HOURS

Family Justice Integration Analysis

Cross-domain analysis comparing CMS maintenance enforcement with Family Court contact order resolution. AML identified systematic differences in enforcement speed and mechanisms.

Data Sources 2
Contradictions 4
Duration 2 hours
CRIMINAL JUSTICE • 1 MARCH 2026 • 6 HOURS

Criminal Sentencing Analysis

Geographic sentencing disparity analysis using MoJ Crown Court data. AML detected variance patterns in sentencing outcomes across police force areas. Phase 1: geographic disparities published. Phase 2: demographic analysis held pending peer review.

Records 1,067,545
Published 4 geographic
Duration 6 hours

Domain Agnostic Architecture

Beyond Policy Analysis

AML operates as a mathematical governance layer independent of domain, language, or platform. The same deterministic engine that detected contradictions in family law can govern any system requiring rule-based validation.

Because AML translates to target implementation languages, governance rules written once can execute across different technology stacks, operating systems, and platforms. This enables consistent governance regardless of underlying infrastructure.

Application Areas

Proven
AI governance — deterministic safety layer for AI model outputs (whitepaper published, 56 tests passing)
In Development
Healthcare systems analysis — consistency between clinical guidelines and operational outcomes
In Development
Financial compliance — automated regulatory rule validation across transaction systems
In Development
Cross-platform application governance — single governance layer across multiple operating systems

The translation capability means AML governance can execute identically whether the underlying system runs on TypeScript, Python, Swift, Kotlin, or any other language. Write governance rules once. Deploy everywhere.

Methodology

Same Engine, Different Domains

Each analysis follows identical governance principles. AML modules define thresholds and validation rules. The executor applies those rules deterministically. The audit system logs every decision.

Data extraction, rule execution, and contradiction detection are automated. Analysis time includes module creation, data processing, and dashboard generation.

Traditional research timelines for equivalent analysis: 6-12 weeks. AML-governed analysis: same day.

Reproducibility

Verify The Findings

All source data is publicly available from gov.uk. AML modules are provided for transparency. Results are published in machine-readable formats.

The OS Infinity governance engine is proprietary. Enterprise licensing available for deployment across regulatory compliance, policy analysis, audit use cases, and cross-platform application governance.