Models that survive production
Most ML projects fail after the notebook. We design data pipelines, monitoring and retraining from the start.
Common use cases
- Demand and inventory forecasting
- Fraud and anomaly detection
- Product recommendations and search ranking
- Visual inspection and shelf analytics
What we do
Forecasting
Demand, supply and capacity forecasting.
Computer vision
Defect detection, shelf audits and OCR.
Recommendations
Personalised ranking for commerce and content.
MLOps
Automated training, deployment and drift monitoring.
How we deliver it
Baseline
Measure today’s accuracy and cost.
Model
Train and compare candidate models.
Productionise
Pipelines, APIs and monitoring.
Improve
Scheduled retraining and A/B tests.
Last updated