Machine Learning & Predictive AI Pipelines Australia & NZ
Custom machine learning models, PyTorch pipelines, predictive analytics, and MLOps deployment for enterprise companies in Australia and New Zealand.
Operational Value from Raw Data
Collecting massive data points is useless without custom predictive logic. We build pipelines that analyze data streams and run low-latency inference models directly inside your production flow.
Feature Store Pipelines
Automating data cleaning, formatting, and aggregations to feed real-time prediction engines.
Inference Latency Optimization
Compiling models using ONNX or TensorRT to maintain sub-50ms inference times on server arrays.
Data Science & MLOps
From mathematical modeling to scalable model registry and tracking infrastructure.
Custom Predictors
Building custom regression, clustering, and classification models using XGBoost, PyTorch, or TensorFlow.
ML Pipelines
Automating model retraining loops on Kubernetes to avoid data drift performance decay.
Analytics Engines
Deploying dashboards that track model metrics, feature importances, and business ROI.
Inference Servers
Scaling low-latency Triton or FastAPI model hosting systems behind API load balancers.
"Their ML model predicted equipment failure 12 hours in advance. This single implementation saved our manufacturing line over $200k in downtime costs last quarter."
Robert Vance
VP of Operations, IndusCorp
Predictive Implementations
Turning raw telemetry and event streams into automated operational actions.
Dynamic Pricing System
Inference engine that adjusts SaaS subscription pricing and discounts dynamically based on user session telemetry.
IoT Predictive Maintenance
Real-time streaming pipelines analyzing machinery temperature and vibratory data to schedule maintenance alerts.
Machine Learning Pricing
Prove the idea works on your data before committing to a full build — each stage is priced separately so you can stop at any point.
Feasibility Study
Find out whether your data can actually support the idea.
- Data quality and volume assessment
- Baseline model on your real data
- Accuracy expectations and limitations
- Build-vs-buy recommendation
- Written findings with go / no-go call
Model Development
A trained, evaluated model deployed behind an API.
- Everything in Feasibility Study
- Data pipeline and feature engineering
- Model training, tuning, and validation
- Deployment behind a production API
- Batch or real-time inference setup
- Performance benchmarking and documentation
MLOps Retainer
Models degrade quietly — this is how you catch it.
- Model drift detection and alerting
- Scheduled retraining pipelines
- Data quality monitoring
- Experiment tracking and versioning
- GPU cost optimisation
- Included development hours each month
All prices in NZD and exclude GST. Cloud compute and GPU training costs are billed at cost, separately from the fees above.
Frequently Asked Questions
Clear answers about delivery, technology, compliance, and scope across Australia, New Zealand, and global engagements.
We specialize in PyTorch, TensorFlow, scikit-learn, XGBoost, and Hugging Face Transformers. We train custom regression, classification, computer vision, and time-series forecasting models.
Unlock predictive operations?
Request a technical data audit to evaluate your features and training preparedness.
Request Data Audit