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Route Optimization algorithms
You will save hours of work, spend less fuel, and optimize your logistics.
Normally deliveries are made by intuition of time and distance. Artificial intelligence will tell you exactly the order of deliveries to follow and what route you have to take based on traffic conditions, kilometers and the weather.
save time and money
We develop customized models adapted to each client, although they are all based on a common training base: our Clintell Smart Routes (CSR) algorithm.
CSR is trained periodically with data from Google Maps, a weather API, and real urban distances. Starting from this base, we will later add information about your own vehicles and routes.
Deliver faster, save time and money
- Fuel savings
- Delivery time optimization
- Less kilometers traveled
- Fewer delivery hours
You don’t need a big dataset
Save time, save money
Once the usual routes of the business have been consulted, we test and train the model with traffic data from Google Maps, distances from the usual distribution areas, type of distribution vehicles, and external variables (weather, important events, etc.)
It is not necessary to have a large volume of initial data since these algorithms are mainly fed from external sources. The only essential thing will be to know the usual routes and the type of vehicles used, to focus and train the model in the areas of interest.
From intercity to
last mile deliveries
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