AI & Predictive Modeling
AI in the engine room, not the pitch deck.
You cannot model on data you can't reconcile, so we treat data quality as the first AI deliverable. Then we apply AI where it compounds: entity resolution, predictive analytics on operational history, and intelligent process automation wired into the tools your teams already use.
- Feature stores
- Predictive models
- LLM automation
- Evaluation harnesses
Best for
Executive and operational teams with a defined AI opportunity but uncertain data readiness.
Where it usually starts
There is pressure to use AI, but no defensible view of which use cases the current data can support.
First phase
2-week readiness audit; 6–8 weeks to a first production model
Indicative investment
From $9k + GST
What we deliver
- Data quality and entity-resolution pipelines
- Forecasting and propensity models with monitored drift
- Document and process automation with human review paths
- Model explanations surfaced inside operational workflows
Enterprise FAQ
- How long before a model is production-ready?
- A first predictive model typically ships within 6–8 weeks, including feature engineering, validation, and a monitored inference endpoint. We prioritise a measurable business outcome over a perfect benchmark.
- How do you handle data privacy and model governance?
- We train and run models inside your environment or a dedicated tenant. PII is masked or excluded from training data, and we maintain model cards, version control, and drift monitoring for auditability.
- What exactly do we receive at handover?
- A versioned model, feature pipeline, inference API, evaluation harness, monitoring dashboard, and runbook. Your team can retrain, debug, and extend the model without relying on us.
- How do you manage model risk?
- Every model ships with a holdout evaluation, bias checks where relevant, and a human-in-the-loop path for low-confidence predictions. We define clear fallback rules before the model makes any automated decision.
Related capabilities
Most engagements combine more than one layer. These are the ones that most often sit alongside AI & Predictive Modeling.