Machine Learning Development
Custom machine learning models for prediction, classification, recommendation and forecasting, taken from data all the way to production, with the MLOps to keep them reliable.
Machine learning, all the way to production
A model in a notebook is not a product. The value of machine learning shows up only when a model is integrated into a decision or workflow and kept accurate as the world changes.
We build custom models for your problem, deploy them into your systems, and put the monitoring and retraining in place so they keep earning their place after launch.
- Custom models tied to a real decision or workflow.
- Deployed into your systems, not left in a notebook.
- Monitoring and retraining so accuracy holds over time.
What we build
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Prediction and forecasting
Models for demand, risk, churn and other outcomes, tied to the decisions they are meant to improve.
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Classification and recommendation
Classification, ranking and recommendation systems built on your data and evaluated on your metrics.
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Deployment and MLOps
Deployment, monitoring and retraining so models stay accurate as data and behaviour shift.
Frequently asked questions
Do we have enough data?
Often yes. We assess data readiness early and are honest about what a model can and cannot do with what you have, before any build starts.
What happens after launch?
We monitor for drift and retrain on a schedule or trigger, so accuracy holds up instead of quietly degrading over time.
How is this different from generative AI?
Machine learning predicts and classifies from your structured data; generative AI produces text and content. We build both and often combine them.
Turn your data into decisions
Tell us the outcome you want to predict or improve. We will scope a model and the path to run it in production.