Predictive cold-chain oversight

Give every shipment a live freshness heartbeat for distribution command centers

SpoilSafe unifies real-time sensing with machine learning that predicts hours-to-spoil for distributors, transporters, and retailers - giving teams the confidence to act before loss touches the balance sheet.

Our predictive freshness models simulate every pallet and lane in real time so you always know the time remaining to intervene.

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$1T+
global food waste every year
1/3
of food lost before it’s eaten
+18h
average ML warning window

$1 Trillion

in food goes to waste around the world every year.

450 Million

tons of food vanish across retail and hospitality before reaching consumers.

11.6%

of all food is lost to spoilage throughout the distribution chain.

1/3

of all food produced never gets eaten due to invisible spoilage.

SpoilSafe’s machine-learning forecasts turn guesswork into foresight so teams prevent loss instead of reacting to it.

Predict hours-until-spoil before quality declines

SpoilSafe's ML models predict freshness degradation in real-time—just like this banana's visible transformation. Get hours-until-spoil forecasts to optimize pricing, routing, and inventory decisions while products are still profitable.

ML Prediction Active

Predictive models tracking degradation patterns across your supply chain.

What You Get

Predictive freshness intelligence you can act on

Predictive command center

Command intelligence for cold-chain leaders

Live command log Auto capture
  • 07:12 · Dock 4 – humidity vent cycle initiated
  • 07:18 · Route 12 – ETA synced with retailer HQ
  • 07:22 · Cold room 2B – purge completed
  • Chicago DC holding premium tier
  • Dallas markdown triggered for ripening produce
  • Newark partner promo synced to retailers
Dynamic pricing AI indexed
  • Chicago DC $18.40 / crate
    Freshness 92% +18h buffer
    Action: hold premiums, monitor ML cues
  • Dallas DC $15.60 / crate
    Freshness 78% 4h to intervention
    Action: prep markdown + QA sweep
  • Newark DC $19.20 / crate
    Freshness 88% +11h buffer
    Action: stage labor for rotation

SpoilSafe's predictive models trigger markdowns when freshness dips below 80% and push premiums while ML forecasts show 90%+ integrity.

On-time routes 97%
Active risk flags 4
Cases per hour 1,240

Network-wide monitoring

Track temperature, humidity, and gas composition across depots, trucks, and stores—feeding the ML engine that forecasts spoilage hours ahead.

Predictive alerts

Machine learning forecasts shelf-life, flags excursions, and shares time-to-rot countdowns by role and severity so teams know exactly when to intervene.

Adaptive insights

Recommendations evolve with every sensor reading, balancing freshness, labor, and logistics constraints using continuously trained predictive models.

Enterprise-grade security

Encryption, RBAC, and audit trails keep sensitive operational data compliant from supplier to storefront.

Flexible hardware

Deploy compact sensors in containers, walk-ins, and trucks—installation is plug-and-play with industrial resiliency.

Scalable architecture

Manage every location from a unified dashboard—aligned with ERP, inventory, and QA workflows for enterprise scale.

Ready to align distribution, transport, and retail on freshness?

Discover how SpoilSafe’s predictive ML engine gives every operator visibility, actionable SOPs, and measurable ROI.

Explore the Vision