Machine Learning.
Forecasting, classification, anomaly detection, computer vision and recommenders — engineered into your processes, not parked in a notebook.
ML where it moves a number.
We pick ML problems where the outcome is observable and commercial — not where it's fashionable. Demand forecasting that reduces waste. Anomaly detection that cuts fraud losses. Propensity models that lift conversion. Vision systems that automate inspection.
And we engineer them. MLOps, monitoring, retraining, drift detection — so the model that ships is still the model in six months.
What we build.
Forecasting & demand planning
Hierarchical, intermittent, promotional — whatever your SKU profile needs. Probabilistic, not point forecasts.
Classification & propensity
Churn, conversion, claim risk, credit risk. Calibrated probabilities, not just accuracy.
Anomaly & fraud detection
Unsupervised and supervised pipelines with human-feedback loops for continuous improvement.
Recommenders & segmentation
Personalisation for product, content, next-best-action. Online evaluation, A/B by design.
Computer vision
Inspection, OCR, defect detection, counting. Edge-deployable where needed.
MLOps platform
Feature store, experiment tracking, model registry, CI/CD, monitoring, retraining — the plumbing that keeps models trustworthy.
Discover → model → deploy → monitor.
Framing
Business outcome, labels, evaluation metric, baseline, success bar.
Modelling
Feature engineering, model bake-off, offline evaluation against baseline.
Engineering
Productionisation, integration, monitoring, A/B harness.
Operate
Drift alerts, retraining cadence, performance attribution.
- ✓Production model pipelineTraining, inference, monitoring — in your cloud.
- ✓Evaluation reportAgainst baseline, slice-by-slice, calibration.
- ✓Model cardsIntended use, limits, risks, data lineage.
- ✓Integration into business processNot a dashboard — a decision.
- ✓Retraining runbookTriggers, process, ownership.
- ✓Business-case evidenceBefore/after, A/B results, financial impact.
Tools & frameworks we use.
A real engagement.
Manufacturing — predictive maintenance on a 260-machine estate.
A mix of gradient-boosted and LSTM models trained on telemetry and maintenance logs cut unplanned downtime by 34% and extended MTBF by 2.1×. ROI inside the first year.
Read full case study