Three specialized AI models protecting players across responsible gaming, fraud detection, and anti-money laundering — deployed on your terms.
Your data. Your models. Your platform.
Global gambling revenue facing regulatory tightening
US states with legal sports betting
Regulatory penalties in H1 2025 alone
The responsible gambling industry faces three critical limitations:
A vertically integrated platform combining behavioral AI, MLOps, agentic delivery, and regulatory compliance.
Three proprietary AI models — ORBIT, AEGIS, and TRace — that analyze behavioral patterns, not just transactions. Built on a shared hierarchical transformer architecture specialized for responsible gaming, fraud detection, and AML compliance.
Full model lifecycle management — register, train, evaluate, deploy, and monitor. On-premise deployment for jurisdictions requiring data sovereignty like New York and tribal operators. Your models, your infrastructure.
A team of 10 specialized AI agents autonomously develop, test, and iterate on the platform through a continuous delivery loop. Describe features in plain English — the PM agent decomposes tasks, engineers implement in isolated worktrees, QA validates, and the cycle repeats until all quality gates pass.
Pre-configured for 38+ US states with jurisdiction-specific rules. Meeting AI/algorithmic trigger requirements in NY, NJ, CO, MA, and NC out of the box. Cryptographically signed audit trails and full data sovereignty.
A unified hierarchical transformer architecture specialized for responsible gaming, fraud detection, and anti-money laundering — running in parallel on every player event.
Operator Risk Behavioral Intelligence Transformer
Hierarchical transformer processing events at three levels with 29 behavioral features aligned to DSM-5 gambling disorder criteria. Detects loss-chasing, session escalation, and self-exclusion risk.
Prediction Tasks
Adaptive Event-Graph Intelligence System
Extends ORBIT with 9 fraud-specific features and a gated fusion mechanism. Detects bonus abuse, bot activity, organized fraud rings, and identity theft through behavioral and transactional signals.
Prediction Tasks
Transaction Risk Analysis & Compliance Engine
Processes 11 AML-specific transaction features including structuring pattern detection, wagering ratio analysis, and rapid fund movement tracking. Monitors transaction, session, and account hierarchy.
Prediction Tasks
All three models share a common hierarchical transformer backbone but specialize through domain-specific embeddings, features, and task heads. They run in parallel on every player event with unified risk scoring and rule-based fallbacks.
Event Ingestion (REST / NDJSON / WebSocket)
→ Event Bus (Redis Streams)
├→ ORBIT → risk, chasing, exclusion, anomaly
├→ AEGIS → fraud class, bonus abuse, bot, identity
└→ TRace → AML risk, structuring, velocity, layering
→ ML Service (FastAPI) → Backend API → Dashboard
AIRG is built and continuously refined by a team of 10 specialized AI agents operating in an autonomous delivery loop. This isn't just a development methodology — it's the core of how the platform evolves.
PM analyzes findings, creates prioritized tasks
Engineers implement in isolated git worktrees
Automated browser + unit tests with severity reports
Zero blockers = approved; otherwise re-iterate
A Product Manager agent orchestrates 9 specialist engineers. Each agent is a domain expert with its own tools, context, and responsibilities.
Story-Driven Development
Describe what you need in plain English with acceptance criteria. The PM agent decomposes the story into concrete tasks, assigns to specialist agents, and manages the full delivery lifecycle — no manual intervention until all quality gates pass. Real-time observability through the admin dashboard shows agent activity, task progress, QA findings, and delivery history.
Every prediction is explainable. Feature importance breakdowns and DSM-5 clinical alignment ensure regulators and operators understand why.
Cryptographically signed audit trails, jurisdiction-specific retention policies, and AES-256 encryption at rest and in transit.
Detecting at-risk players across three risk dimensions — problem gambling, fraud, and money laundering — before transactions tell the story.
Pre-configured for 38+ US states. Meeting AI/algorithmic trigger requirements in NY, NJ, CO, MA, and NC out of the box.
“We built the data and AI infrastructure for one of America's largest gaming companies. We lived the problem every day — vendor lock-in, black-box decisions, cloud-only limitations. AIRG was built to give every operator the tools to protect their players on their own terms.”
— AIRG Founding Team
Schedule a personalized demo and learn how three AI models can protect your players across responsible gaming, fraud, and AML.