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SpoilSafe provides cold-chain oversight by unifying real-time sensing data with machine learning to predict the hours-to-spoil for perishable goods. This system offers distributors, transporters, and retailers predictive freshness models that simulate pallet and lane conditions to enable proactive intervention. The platform delivers network-wide monitoring and adaptive insights, allowing operations to optimize routing and inventory based on forecasted degradation patterns.
Updated 2 months ago
Funding
Funding not disclosed
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Founders
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Product
Features
- SpoilSafe unifies real-time sensing with machine learning to predict the hours-to-spoil for perishable goods across the cold chain. The platform provides network-wide monitoring of environmental factors like temperature and humidity to generate predictive freshness forecasts. This allows distributors, transporters, and retailers to intervene proactively, optimizing routing and inventory to minimize food waste.