Predict, Optimise & Act With Confidence
Custom machine learning models trained on your data — forecasting demand, detecting anomalies, predicting churn, and surfacing insights that drive competitive advantage.
Custom Models Trained on Your Data
Off-the-shelf AI models are trained on generic data. Custom machine learning models are trained on your data, in your context — delivering predictions that are specific, accurate, and directly actionable for your business.
Demand Forecasting
Predict future demand for products, services, or resources — reducing stockouts, overproduction, and the cost of uncertainty.
Customer Churn Prediction
Identify which customers are at risk of leaving before they do — enabling proactive retention campaigns with a measurable ROI.
Anomaly Detection
Automatically identify outliers, fraud, equipment failures, or unusual patterns in your operational data — before they become costly problems.
Predictive Maintenance
Use sensor and operational data to predict equipment failure before it occurs — reducing downtime, extending asset life, and lowering maintenance costs.
Natural Language Processing
Extract meaning from unstructured text — categorise support tickets, summarise documents, analyse sentiment, or classify content at scale.
Model Monitoring & Retraining
All models drift over time. We implement monitoring pipelines that track performance and trigger retraining when accuracy degrades.
The ML Development Lifecycle
Data Preparation
We assess data quality, engineer features, and build the clean datasets needed to train reliable models.
Model Development
We explore multiple algorithms, tune hyperparameters, and validate performance against your business requirements.
Production Deployment
We package the model as an API or embed it directly into your existing systems for seamless integration.
Monitoring & Retraining
We set up ongoing performance monitoring and scheduled retraining pipelines to keep the model accurate over time.
Explainability
We provide clear documentation of how the model works and what factors drive its predictions — important for compliance and trust.
Team Handover
We train your team to understand, maintain, and build confidence in the models we deploy.
Data Requirements
You don’t need to have perfect data to get started — but you do need enough of it. Here’s a general guide.
Minimum Data Requirements
For most supervised ML models, we typically need at least 12 months of historical data with a reasonable number of labelled examples (e.g. for churn prediction: at least a few hundred examples of customers who churned).
Not sure if you have enough? Book a free consultation and we’ll assess your data in confidence.
All Data Stays in Australia
All modelling work and data processing is performed on Australian-hosted infrastructure. Your data never leaves Australia, and we operate under strict data handling agreements.
We’re aligned with the Australian Privacy Act, the Notifiable Data Breaches scheme, and the AI Ethics Principles.
Let’s Start Your AI Journey
Whether you’re exploring AI for the first time or scaling existing capabilities, our team is here to help. Book a free consultation with our Australian-based AI specialists.