Machine Learning
Forecasting, recommendations, NLP and computer vision. We build and deploy ML systems that create measurable business value — not just model experiments.
What we build.
ML model predicting product demand/seasonality for e-commerce or retail brands to optimise inventory and reduce stockouts/overstock.
Predicts which customers are likely to churn based on behaviour patterns, enabling proactive retention campaigns — includes a scoring dashboard for the client's team.
"You might also like" style recommendation system for e-commerce or content platforms, built on collaborative filtering or embedding-based similarity.
Computer vision model for brands needing automated visual QA — e.g., product defect detection, brand-logo compliance in user-generated content.
ML-driven pricing engine that adjusts prices based on demand, competitor pricing, and inventory levels for e-commerce clients.
Models built for the real world.
Every ML project starts with defining the business metric we're optimising for — not just model accuracy. We iterate on features, run offline and online evaluations, and ship models into production with monitoring, retraining pipelines, and drift detection built in.
E-commerce and retail brands looking to optimise inventory or personalise at scale. B2B companies wanting to predict churn or lifetime value. Any business with enough historical data to make predictions that improve decisions.
Ready to build?
Ready to build what's next?
Tell us about your product. We'll come back with a plan, a team and a timeline.