InvSightOS
Problem: inventory decisions are harder when information is scattered, delayed, or difficult to interpret.
How it works
Bring the available inventory information into a clearer decision view, review what is known, and discuss the next action for the operation. No live connector or integration is assumed here.
Intended outcomes
Clearer inventory information to support practical inventory decisions.
Buyer fit
InvSightOS applies human judgment amplified by AI speed. Managers direct the strategic goal while AI informs the tactical choice. People decide what to count, expedite, or reorder. There is no autonomous purchasing or direct ERP changes; human intelligence guides every inventory action.
Disruption Risk
For teams working to make inventory decisions with the information already available to them.
Cycle Count Prioritization
Prioritize cycle counts by inventory risk and data uncertainty. Focus resources where count history and demand signal conflict.
Evidence-Based Replenishment
Project stock levels and recommend replenishment timing and quantities based on lead times and consumption history, with evidence supporting each recommendation.
