Predictive modelling
We build regression and classification models on your historical data, then deploy them behind an API your existing software can call. Typical turnaround: four to eight weeks from first data handover to production endpoint.
Three organisations we worked with in 2024 cut manual data processing time by between 38% and 61%. One logistics firm in Belfast rerouted its fleet scheduling through a reinforcement learning model we built in nine weeks. The savings paid for the project twice over within six months.
"They didn't pitch a product. They sat with our warehouse team for a week, then told us exactly which problem was worth solving first." Operations director, NI-based distribution company
We build regression and classification models on your historical data, then deploy them behind an API your existing software can call. Typical turnaround: four to eight weeks from first data handover to production endpoint.
Document classification, entity extraction, sentiment scoring. We fine-tune transformer architectures on your domain vocabulary so the model understands your industry jargon, not just generic English.
Defect detection on production lines, document digitisation, inventory counting from camera feeds. We handle annotation, training and edge deployment.
Before any model work begins, we audit your data estate. Where is it stored, how clean is it, what governance exists? A two-week assessment produces a ranked list of AI opportunities with estimated ROI for each.
Models are only useful if they stay fresh. We design and maintain automated retraining pipelines using Airflow, Kubeflow or managed cloud services, depending on your infrastructure preferences.
Not every organisation needs a custom model. Some need a strategy document. Others need a production system maintained for years. The matrix to the right helps you compare.
If you are unsure, start with a diagnostic. It costs less than two days of consulting time and gives you a clear recommendation.
| Engagement | Duration | Deliverable | Best for |
|---|---|---|---|
| Diagnostic | 1–2 weeks | Opportunity report with ROI estimates | Organisations exploring AI for the first time |
| Proof of concept | 4–6 weeks | Working prototype on real data | Teams that need internal buy-in before committing budget |
| Production build | 8–16 weeks | Deployed, monitored model with API | Companies ready to integrate AI into live systems |
| Retained support | Ongoing | Model monitoring, retraining, drift alerts | Organisations that lack in-house ML engineering capacity |
We start by listening. The first meeting is about your operation, not our technology. We ask what decisions cost you the most time or money, where errors cluster, and what data you already collect.
Then we do something unusual: we tell you what not to automate. Some processes are better left manual. Others need better data collection before any model will help. Honesty here saves months of wasted effort.
When we do build, we pair one of our ML engineers with someone from your team. Knowledge transfer is built into the project, not bolted on at the end. By handover day your staff can explain the model's logic to auditors, retrain it on fresh data, and know when to call us back.
Post-deployment, we monitor model performance weekly for the first quarter. Drift happens. Seasons change, customer behaviour shifts, suppliers alter packaging. We catch degradation early and retrain before it affects your bottom line.
Tell us what you are trying to solve. We will respond within one working day with an honest assessment of whether AI is the right tool, and if so, which engagement type makes sense.
473 Jerome Court, West Lind Park, Northern Ireland, HE38 8RY, United Kingdom
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Last updated: January 2026.
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Last updated: January 2026.
Results described on this site, including percentage improvements and cost savings, are based on specific client engagements and are not guaranteed for future projects. Every organisation's data quality, infrastructure and business context is different, and outcomes will vary.
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Last updated: January 2026.