Advanced machine learning techniques, big data technologies, genetic algorithms, and data engineering is used to plan the most optimal route while keeping the factors like customer delivery schedules, transportation method, time, and costs into consideration. Additionally, our Automated Route Optimization system takes several real-time inputs like feedback from agents & drivers, ETA, etc. to keep on re-optimizing the routes.

Deep learning and cognitive computing drives our robust constraint engine which intelligently identifies the availability of exact number of transportation units and where to domicile them at a particular time. Following constraints are taken into account to customize a superior route -

• Static and dynamic real-time constraints
• Domain-specific pre-packaged constraints
• User-specified priority and applicability of constraints
• e.g., constraint of an individual delivery point, or routes or direction specified by the client

Late freight swapping services can greatly help if you want to add or delete a delivery point at the last moment. Our route optimization system allows you to quickly add or delete one or more delivery points even when your vehicles are out for delivery.

If you have dynamic service timings, we can provide you with predictive traffic route optimization and recurring route optimization. This helps you to choose the best possible routes for your deliveries, thereby reducing delivery time, and improve your bottom line.

User-specific reports are created which contain detailed account of experiments with multiple levers on constraint types and optimize cost, number of visits, distance travelled, fleet size, etc. to ensure quick & measurable ROI. These reports reduce overall time for planning or long-term planning, and also assist in efficiently tracking fleet and on-the-go workforce.

This feature directs your vehicles to the closest and most affordable location to replenish fuel, compressed gas, etc., preventing your vehicles from going all the way back home to re-fuel amidst deliveries, thereby, saving time, fuel consumption, and money.

Automated route planning and automated route selection allows you to quickly assign and re-assign delivery routes, thereby helping you to increase the number of deliveries per day, resulting in savings amounting to 30% in distance, 20% in the number of routes, and 25% in travel time.

If you already have in-house applications for route optimization, then we can assist you in developing APIs for your in-house apps. This helps to reduce fuel and operational costs, keep a check on frauds, and improve sales due to prompt and timely delivery.