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AI DECISION SUPPORT

Operational recommendations for sales, services, stock planning, and next-step decisions.

Decision support is useful only when it explains what is happening, why it matters, and what action a real operator should take next. This page makes that layer easier to review.

Best use: understand how forecasts, model confidence, and business signals can support daily planning without replacing human judgement.

Discuss AI Use Open Platform Overview
Decision logsReview where the system is making recommendations and what business area each recommendation belongs to.
Forecast viewUse forecast cards to check direction, horizon, and model status before acting on an assumption.
Operator controlThe goal is guided support, not blind automation. Staff should still understand the decision before using it.

Sales signals

Decision support can help surface demand patterns, product interest, and timing clues that improve quotation or product discussion quality.

Service forecasting

When service categories begin to rise, this layer should help the team prepare workload, tools, and support readiness earlier.

Inventory planning

Product movement, repeat issues, and category demand can guide smarter stocking instead of last-minute buying decisions.

How to read this page

  • Start with decision logs to see what area the system is watching.
  • Check forecast cards to understand the planning signal and horizon.
  • Use the result as guidance, then confirm it against real business conditions.

DECISION LOGS

Current recommendation signals

This section is loaded from the real decision-support endpoint. If the feed fails, the page should show that honestly.

FORECASTS

Model and forecast outputs

These cards help the team understand prediction domain, current model status, and forecast horizon before taking action.