Data Science & ML
Predictive models, forecasting and machine learning — built on your data, delivered to production standard.
What we deliver
Most ML projects don’t fail because of the algorithm. They fail because the model never makes it out of a notebook — scoped too broadly, or disconnected from the business process it was meant to improve. As a machine learning consulting team, we build models that run in production: validated against your outcomes, integrated into your workflows, and maintainable by your team.
Predictive modelling
Forecasting, classification, clustering and anomaly detection — built on your data and validated against your business outcomes. From churn models to demand forecasting to pricing engines.
Time-series forecasting
Advanced time-series models incorporating complex business logic, macroeconomic variables and scenario modelling — giving leadership reliable forward views, not just historical reporting.
Customer & behavioural analytics
CLV modelling, segmentation and propensity scoring — identifying the customers worth retaining, targeting or acquiring, and giving your marketing team the signals to act on it.
Pricing & risk modelling
Actuarial and pricing models built for insurance, financial services and risk-intensive industries — replacing legacy GLMs with modern, scalable approaches that improve accuracy and auditability.
ML model operations
Model deployment, monitoring, evaluation frameworks and drift detection on platforms like Azure Machine Learning — so your models stay accurate, auditable and maintainable in production.
ML model migration
Migration of legacy models and statistical workflows — SAS, R, SPSS — to modern platforms like Databricks or Python. Rebuilt to production standard, with full validation against original outputs.
Machine Learning Consulting Services in Australia
How we approach it
Start with the business problem
We don’t build models for their own sake. Every engagement starts with a clear definition of the decision the model needs to support and the outcome it needs to improve — so we’re optimising for the right thing from day one.
Build on your existing data
A model is only as good as the data behind it. We start with what you already have — cleaning, structuring and engineering features before a line of model code is written.
Deliver to production standard
We don’t hand over a notebook. Every model is deployed, monitored and documented — with a structured handover so your team can maintain, retrain and extend it without us.
