Applied AI that turns
Data into dependable decisions.
ARGenesis Artificial Intelligence services cover the full stack: classic AI and rule engines, machine learning, deep learning, optimisation and decision systems. We help organisations design, build and govern AI that is explainable, auditable and tightly aligned to business outcomes.
Classic AI · ML · Deep learning · Optimisation
Grounded in regulated, data‑rich environments
AI services snapshot
Decision & rule systems
Business rules, triage, eligibility & routing.
Deterministic
Predictive modelling
Supervised ML for risk, churn, demand & more.
Probabilistic
Optimisation & operations
Resource, portfolio & process optimisation.
Prescriptive
We can deliver standalone AI solutions or embed them within platforms such as GenieAPP, GenieLab and GenieUs, and your existing systems.
How we think about AI services
Start from decisions, not algorithms.
We begin with the decisions you’re trying to improve — underwriting, claims, pricing, operations, customer journeys — then shape AI solutions that add signal, not noise. Technology choices follow from the problem, risk and governance constraints.
Where we help
- Translating business challenges into AI problems
- Identifying where rules, ML or optimisation fit best
- Building explainable and auditable AI components
- Connecting AI outputs into day‑to‑day workflows
How we work
- Joint discovery with business, data, risk & IT
- Clear phases: explore, prove, industrialise
- Patterns & components re‑used across use cases
- Documentation, knowledge transfer & training
AI service lines
From rules and models to full decision systems.
You can start with a single use case, or design a broader AI roadmap. Each service line can be delivered standalone or as part of a combined engagement.
Rules & decision engines
• Eligibility, triage & routing rules
• Business rule libraries & governance
• Integration with portals, workflows & APIs
Predictive & ML modelling
• Risk, propensity, churn, demand & uplift models
• Feature engineering & performance monitoring
• Bias, fairness & stability assessment
Optimisation & operations research
• Resource, capacity & scheduling optimisation
• Portfolio & pricing optimisation frameworks
• Scenario & constraint analysis
AI platform & ecosystem design
• Data & model pipelines with MLOps
• Integration with GenieLab & AI ecosystem
• Monitoring, alerting & lifecycle management
AI governance enablement
• Policies, standards & model documentation
• Training for teams on using AI safely
• Support for committees, boards & regulators
Cross‑industry AI examples
Practical AI use cases we can help design and deliver.
Insurance
• Underwriting triage & appetite rules
• Claims routing & prioritisation models
• Fraud, leakage & anomaly detection
• Operational & capacity planning optimisation
Healthcare
• Risk stratification & pathway support
• Referral, waiting list & capacity optimisation
• Operational forecasting & planning
Retail & digital
• Churn, propensity & next‑best‑action models
• Demand, inventory & fulfilment optimisation
• Recommendation & personalisation engines
Education & public sector
• Case triage & routing logic
• Resource & scheduling optimisation
• Analytics & forecasting for planning
Next step
Shape an AI engagement grounded in your decisions and constraints.
Whether you are at the start of your AI journey or looking to modernise existing models and rules, we can help you scope a right‑sized AI engagement with clear outcomes, risks and governance.
Experience across insurance, health, retail & public sector
Decision‑first, governance‑first AI delivery
Ready when you are
Share a little about your organisation, decisions and constraints, and we’ll propose 1–2 AI service options that fit your context.
Not ready for a project? We can start with a strategy or awareness session for your leadership, board or working group.