Machine Learning & Predictive Analytics — AI & Data

All AI & Data

Prediction earns its keep when it changes what someone does. We built the forecasting that moved a national tower network from reactive to preventive maintenance, and the decision engine sitting at the centre of a UK digital bank. Both are live, and both are measured.

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What we build

Failure & demand forecasting

Predicting outages, consumption and load ahead of time so maintenance and capacity become planned work rather than emergencies.

Risk & credit scoring

Models that score applications and exposures, built for the explainability a regulator or credit committee will ask for.

Customer segmentation

Behavioural segmentation that drives targeted marketing, personalisation and tailored advice rather than a broadcast.

Anomaly & fraud detection

Spotting the transactions and events that do not fit the pattern, with thresholds tuned to the cost of a false positive.

Recommendation systems

Ranking products, content or next-best actions from behavioural signals and business rules together.

Decision engines

Multi-module engines that combine models, rules and projections into a single recommendation a product can act on.

Running in production today

Predictive maintenance at national scale

For Telenor Pakistan's Thunder platform, a machine-learning engine forecasts site outages, battery performance, fuel consumption and grid failures across a distributed tower estate — cutting operational cost by up to 60% and diesel use by 6 million litres a year.

An intelligent decision engine for a digital bank

For Pennyworth, six modules covering net income and segmentation, income and expenditure, net wealth, goals recommendation, financial projections and next best action — delivered on a serverless AWS architecture.