Machine learning models trained on your data, built for real decisions
Prediction, recommendation and anomaly detection models built around your business question, tested against a clear baseline and deployed where your team can use them.
- Decisions made on gut feel
- Forecasts built in spreadsheets
- Fraud and problems spotted too late
- Data you collect but never use
ML & Data Science Systems for your business
We start from the decision you want to improve, then choose the simplest model that beats what you do today.
Demand & sales forecasting
Predict demand, revenue or capacity so you can plan stock, staffing and spend with fewer surprises.
Recommendation engines
Suggest the right product, content or next action for each user based on behaviour and history.
Anomaly & fraud detection
Flag unusual transactions, sensor readings or usage patterns before they turn into losses.
Churn & lead scoring
Score customers and leads so your team spends time on the accounts most likely to convert or leave.
Text classification & NLP
Sort tickets, tag documents, detect sentiment and pull structured fields out of free text.
Computer vision
Detect, count and inspect objects in images and video for quality checks or monitoring.
From first conversation to launch
Frame the problem
We define the decision the model supports and the metric that tells us it is working.
Audit the data
We check what data you have, how clean it is and whether it can answer the question.
Model & evaluate
We build a simple baseline first, then improve on it and show you the results side by side.
Deploy & monitor
We ship the model as an API or batch job, track accuracy over time and retrain when it drifts.
How much data do we need?
It depends on the problem. Some forecasting and scoring models work with a year or two of history; others need more. We audit your data first and tell you honestly if it is enough.
Do we need our own data science team?
No. We handle the modelling, deployment and monitoring, and we document everything so your developers can work with it.
Who owns the model and code?
You do. You get the code, trained models, documentation and access to everything we set up.
How do we know the model is actually better?
We compare it against a baseline, such as your current rule or a simple average, on data the model has never seen, and share the numbers before launch.
Ready to become an AI-first company? Let’s connect.
Build a new platform, or add AI capabilities to existing software, we deliver solutions that work in real operational environments.
Discuss your idea with our team
Custom AI implementation roadmap
No sales pressure