How it works
Normal patterns are established per vehicle, driver or account from historical data. New data that moves far from the pattern is flagged with the reason.
← AI & WhatsApp API
Anomaly Detection
Let the system watch for what looks wrong: unusual fuel use, mileage, idle time, after-hours movement or transactions, flagged to managers before they turn into costs.
What it does
- Baselines learned from your own data
- Flags for unusual fuel, mileage or idle time
- After-hours and out-of-area movement
- Unusual patterns in transactions or orders
- Alerts by WhatsApp, email or app
- Review list for managers
Why it matters
- Fraud and waste spotted early
- Managers review exceptions, not everything
- Fewer surprises at month-end
- Consistent monitoring across the fleet
Good to know
Baselines need a few weeks of history, and early alerts are tuned to avoid flagging normal variations.
Compare platforms
Traditional
Staff manually messaging customers about arrival times and invoices.
With Amancom
Automatic WhatsApp updates triggered by the actual event in the system.
Common question
Does every alert mean fraud? No. It means something is unusual and worth a look; many have normal explanations.
Ready to see it on your own operation?
Tell us your fleet size or your systems and we will put a proposal together.