AI, Data & Automation

Data-backed recommendations. Decisions stay with people.

Data-backed recommendations. Decisions stay with people. AI produces forecasts and anomaly alerts; approval stays with you.

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Problems we solve

01
Data exists, decisions lag
ERP and finance data sit idle while price, stock or collections choices still rely on gut feel.
02
Black-box fear
Leadership will not approve automated decisions whose rationale cannot be seen.
03
Autonomy risk
“Let the system decide” blurs accountability and audit boundaries.

Decision support — not decision-making

AI produces a recommendation, shows its rationale, and leaves approval with people. This page shares the same principle as n8n, AI Chatbot and WhatsApp Chatbot: without claiming autonomous decision-making.

Roadmap

How it works

01
Data
ERP, finance and operations records are read securely.
02
Model / rules
Forecasting, anomaly or scoring is chosen for the use case.
03
Recommendation + rationale
Output is not only a score; influential signals are shown.
04
Approval
The right role accepts or rejects; n8n writes the outcome back to ERP.
05
Monitoring
Accept/reject rates and drift are reviewed regularly.

Example use cases

01
Collections priority
Ranked suggestions for receivables at higher delay risk.
02
Stock alerts
Planning suggestions on stock-out or excess signals.
03
Price / discount
Suggested price bands from historical margin and demand.
04
Anomalies
Early warnings on unusual orders, returns or cost swings.
05
Explainability
A short summary of features and thresholds behind each suggestion.
06
n8n bridge
After approval, notifications, record updates and follow-up tasks automate.

With the AI layer

Chatbots answer questions; n8n connects flows; decision support produces recommendations. All three are layers on the existing backbone — not a separate magic product.

Explore n8n and automation

Data sources