A last-mile logistics operator was scaling fast but losing money on every inefficient route and every failed delivery attempt. DraconX replaced their static routing model with a real-time AI route optimization engine, cutting fuel consumption, slashing failed deliveries, and unlocking the operational efficiency the business needed to grow profitably
The Opportunity
SwiftHaul Logistics operates a fleet of 180 vehicles delivering to 2,000+ pin codes across the Nation for e-commerce, FMCG, and pharmaceutical clients. With delivery volumes growing at 15% year-on-year, the business was scaling its cost base almost linearly with volume a trajectory that made profitability improvement impossible without a fundamental change in operational efficiency.
The core problem was routing. SwiftHaul’s dispatch system assigned delivery routes using a static zone-based model that had been configured two years earlier and never updated to reflect changed road conditions, new residential developments, or evolved customer density patterns. Routes were rarely optimal. Drivers were regularly covering unnecessary distance. And with fuel representing 31% of SwiftHaul’s total operating cost, even modest routing inefficiencies were translating into significant financial losses at scale.
Failed first-attempt deliveries compounded the problem. With no real-time customer communication layer, delivery failures were only reported at end-of day, by which point the window for same-day re-attempt had closed. Each failed delivery generated a second logistics cost with no additional revenue, and in competitive e-commerce SLAs, failure rates above 12% were triggering client contract penalties.
Swift Haul engaged DraconX to redesign the routing and delivery intelligence layer from the ground up — replacing static assignment logic with a real-time AI system that could optimise continuously as conditions changed.
The Solution
Real-Time AI Route Optimisation, Dynamic Re-Routing, and Automated Customer Communication
DraconX built an end-to-end delivery intelligence platform integrating with SwiftHaul’s existing fleet telematics, order management system, and driver mobile application by avoiding the need to replace core infrastructure and focusing instead on building the intelligence layer on top of what already existed.
The AI route optimization engine runs on a rolling basis throughout each operating day. At the start of each shift, it generates optimal multi-stop routes for every vehicle by solving a dynamic vehicle routing problem across 2,000+ delivery points which factors in delivery time windows, vehicle load capacity, driver shift constraints, live traffic data, and historical delivery success rates by pin code and time of day. Routes that would have taken a human dispatcher three hours to build manually are generated in under 90 seconds.
Throughout the day, the engine continuously re-optimises. A traffic incident, a failed delivery attempt, an urgent same-day addition to the manifest, each triggers an automatic re-calculation that updates the affected driver’s route in real time on their mobile device, without requiring dispatcher intervention. Dispatchers shift from manually building routes to monitoring exceptions.
For failed delivery prevention, DraconX built an automated customer communication layer that sends delivery ETAs via SMS and WhatsApp two hours before arrival, with a one-tap reschedule option for customers who cannot receive their delivery. This simple intervention implemented in under three weeks which proved to be the single highest-impact change in reducing failed first-attempt deliveries.
“We were growing fast but not growing well. Every extra kilometre our drivers were covering was money we couldn’t afford to spend. DraconX fixed the root cause.”
The Impact
Profitable Growth: Lower Costs, Higher Throughput, and SLAs Consistently Met
Fuel costs fell by 28% in the six months following platform deployment, primarily driven by route optimization that reduced average kilometers per delivery by 22% and eliminated the idle and backtracking patterns that were invisible in the old static routing model. At Swift Haul’s fleet scale, this reduction translates to annual fuel savings.
Failed first-attempt deliveries fell from 12.2% to 8.4% and 41% improvement that eliminated a significant portion of the double handling cost that had been suppressing margins. The automated customer communication layer accounted for the majority of this improvement, with customers self-rescheduling before failed attempts rather than requiring costly re-dispatch.
Deliveries completed per vehicle per day increased by 19%, enabling Swift Haul to absorb 35% higher delivery volume in the following quarter with only a 12% increase in fleet size by breaking the linear cost-scaling dynamic that had been constraining profitability. Key e-commerce clients noted a measurable improvement in SLA adherence and reduced the volume of penalty deductions for the first time in two years.
DraconX built us the operational intelligence we needed to grow. The fuel savings alone paid for the engagement multiple times over in the first year.”