Machine Learning & Predictive Analytics
Custom ML models for demand forecasting, churn prediction, dynamic pricing, fraud detection and predictive maintenance, deployed into your ERP and apps with MLOps monitoring.
0%
less stock-outs
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better forecast accuracy
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faster insights
Forecast demand, risk and revenue before it happens.
“We reorder stock by gut feeling.”
“We only notice a customer is leaving after they've left.”
“We have lots of data but no predictions.”
- 1
Data audit
Week 1–2
Is the data there, clean and enough to learn from?
You receiveData audit - 2
Baseline model
Week 3–4
A simple model to prove value before anything complex.
You receiveTrained models - 3
Integrate
Week 5–8
Predictions shown inside the screens people already use.
You receiveInference APIs - 4
Monitor & retrain
Ongoing
Accuracy tracked and the model retrained automatically.
You receiveModel monitoring
Have a different question?
Ask an expert- How much data do we need?
- Usually one to two years of history. The data audit tells you honestly whether a model will help.
- Will people trust the predictions?
- Each prediction shows its main drivers, and users can override with a reason that improves the model.
- Where does the model run?
- As a small service next to your ERP, in your cloud or ours.
Tell us about your challenge. A solutions architect will reply within one business day with ideas, not a sales pitch.