Using VUKU for logistics

Managing resources,
maximising utilisation

learn about our platform

Using VUKU for logistics

Managing resources,
maximising utilisation

VUKU for supply chain management

VUKU optimizes myriad links in the supply chain – just one of the industry sectors in which it has already had a proven bottom-line impact.

Supply chain management adapts to continually changing demand. That demand has to be met effectively so that profitability can be maximised and waste reduced to a minimum.

VUKU uses advanced probabilistic modelling techniques to learn from history and create multiple models of possible outcomes each with different demand for resources such as truck scheduling, pallet collection, or taxis and shared rides.

Unlocking profitability with real-world AI

PROWLER.io has taken steps to solve a long-standing problem for the logistics industry. In this whitepaper, we reveal how VUKU can maximise profits - from minimal data - to help realise a potential 25% reduction in transport costs and tens of billions of dollars of identified cost savings across the global pool pallet industry. Our solution is innovative, flexible and eminently scalable - see the white paper here.

Probabilistic Modelling Icon
  • Probabilistic models predict the demand for tomorrow
  • A series of possible tomorrows are simulated (“Monte Carlo” samples)
Reinforcement Learning Icon
Multi-Agent System Icon
  • For each possible “tomorrow”, we solve the resource allocation problem in simulation
  • See the effects of decisions (e.g. number of trucks)

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