Trackvy ML
TrackvyML analyzes RFID and IoT sensor data and anticipates what the operation needs to do.
Brief
TrackvyML combines RFID, IoT and BLE sensor data with machine-learning models trained on the real operation, to answer concrete questions about inventory, assets and processes.
Your data is sovereign. We deploy AI models in private instances, activating them only when your operation requires it, ensuring your strategic information stays within your company.
Where TrackvyML applies
Four areas of application, with measurable results.
From reactive counting to predictive planning. It predicts stock-outs, proposes replenishment and adjusts forecasts for seasonality.
02Detect unauthorized movements with anomaly algorithms, analyze machinery utilization, and identify underused items to inform CAPEX decisions.
03Analyze dwell times, control shrinkage, and predict loss patterns before they become systemic in tools, RTI, and IT equipment.
04Reconstruct how people, items and inventory move. Discover the gap between the written SOP and floor reality. Identify structural bottlenecks.
Core
The models run on your own instance, over your operational data and under your control. The information stays where it is, and the model amplifies what your team already knows how to do.
How we start
Every diagnostic ends with a deliverable defined before we begin.
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