AI for Your Industry

Manufacturing AI is about keeping machines running, catching defects before they reach customers, and optimising the processes that drive cost. We have built predictive maintenance systems that flag equipment failures before they occur, computer vision pipelines that detect defects and inspect product quality on assembly lines, failure prediction models, process optimisation engines that reduce energy consumption, and supply and demand forecasting for production planning — all running in production environments, not pilot mode.

Thin margins, high acquisition costs, and intense competition make AI non-optional in retail. We have delivered fraud models, credit optimisation engines, personalisation systems, price elasticity models, and cross-channel attribution — all in production, all with measurable outcomes.

Financial services and insurance operate under strict explainability requirements — which agentic AI handles better than black-box models. We have built claims liability systems, credit scoring engines, fraud detection pipelines, and lead scoring models that satisfy compliance teams and deliver measurable business outcomes. For health insurers specifically, preventive ML models that predict disease likelihood in patients — hypertension, Type II diabetes — directly reduce future claims costs by enabling early intervention before the condition develops.

Healthcare AI delivers its highest value when it acts early enough to change an outcome. We have led pan-European data science teams building likelihood-of-disease models for hypertension and Type II diabetes — identifying at-risk patients before symptoms emerge, enabling preventive interventions that delay or avoid the disease. Earlier prediction means lower insurance claims costs, lower treatment costs, and better patient outcomes. Healthcare AI must also meet strict explainability and EU AI Act requirements, which we handle as part of the engagement.

High churn rates and saturated markets make retention analytics a competitive necessity in telecom. CLV-driven retention investment and NBO-powered upgrade campaigns deliver measurable improvement on base economics. We have also built enterprise AI platforms for major B2B technology distributors.

Energy retailers and utilities face two distinct pressures: retaining customers in deregulated markets and planning infrastructure around uncertain demand. We build price elasticity models that quantify how customers respond to tariff increases — essential before any pricing decision — and household-level energy usage prediction models that let planners forecast load at granular resolution. We have also deployed churn prediction systems that identify switcher risk weeks before cancellation.

Travel and hospitality companies sit on rich behavioural data — booking history, browse patterns, ancillary choices — but rarely extract its full value. We build models that predict seat and room upgrades, score the likelihood of add-on purchases at each journey stage, identify who will buy membership or loyalty tier, calculate price sensitivity by customer segment, and surface the right next best offer at the right moment. All in production, connected to CRM and booking systems.

Consulting, legal, accounting, and engineering firms generate enormous volumes of unstructured data in proposals, contracts, and client communications. Text mining, agentic AI for knowledge workflows, and structured AI enablement programmes are the highest-value applications. We have built and delivered all three.