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A regional logistics provider managing over 150 delivery vehicles was dealing with frequent delays and rising fuel expenses. Dispatchers used outdated systems that didn’t factor in live traffic or weather. Drivers often followed fixed routes, leading to wasted mileage, missed delivery windows, and client complaints. The lack of dynamic planning created inefficiencies across the fleet.
We deployed a machine learning-based platform that generated optimal routes in real time. The system integrated live traffic data, weather conditions, customer availability, and vehicle capacity. Each morning, dispatchers received updated delivery routes automatically prioritized for efficiency. Drivers accessed routes via a mobile app with GPS and live rerouting features, ensuring minimal detours and maximum punctuality.
By introducing real-time route optimization powered by AI, we helped this logistics company reduce operational costs, improve delivery performance, and enhance the customer experience. The fleet now runs smarter, not harder.
Looking to optimize deliveries and reduce costs in your logistics operations?
Contact us today to learn how we can help.
We were skeptical at first — AI felt like a buzzword. But seeing the case studies on QanaFlow’s site changed that. Their work with companies facing challenges just like ours gave us the confidence to move forward. The results they delivered for others weren’t just impressive — they felt achievable. That transparency made all the difference.
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