Inside Shiprocket’s AI awakening: How the ecommerce shipping unicorn is rewiring itself for an AI first future
Over the past year, Shiprocket has rewired its platform with AI-led decision engines that touch nearly every stage of the delivery cycle. Its carrier allocation system, once rule-based, is now powered by algorithms that evaluate real-time performance, location-level trends, and historical shipment behaviour to determine the best-fit delivery partner for each order.
The IPO-bound Shiprocket, long known as the tech stack behind thousands of D2C brands, is entering what CEO Saahil Goel describes as its “AI awakening,” a decisive shift that will redefine the company from a logistics enabler into a full-stack intelligence layer for Indian commerce. In a detailed conversation with Business Today, Goel outlined how the unicorn is rebuilding its core around AI to solve some of the sector’s most chronic inefficiencies.
At the heart of this transformation is Shiprocket’s belief that traditional logistics scaling—more delivery partners, more nodes, more surface area—is no longer the moat it once was. Instead, the edge now lies in prediction and automation. “The future of logistics is AI-native. Everything else will simply be too slow or too expensive,” Goel says.
Over the past year, Shiprocket has rewired its platform with AI-led decision engines that touch nearly every stage of the delivery cycle. Its carrier allocation system, once rule-based, is now powered by algorithms that evaluate real-time performance, location-level trends, and historical shipment behaviour to determine the best-fit delivery partner for each order. The result is faster deliveries and fewer RTOs, critical for D2C brands operating on thin margins.
One of the biggest breakthroughs, Goel notes, is in NDR (non-delivery report) mitigation. Using generative AI and conversational automation, Shiprocket’s system now interacts with customers to confirm addresses, reschedule deliveries, or detect fraud signals. “This was a huge blind spot earlier. AI gives us the ability to intervene within seconds instead of hours,” he says.
Shiprocket is also building forecasting models that help merchants plan inventory placement, anticipate demand spikes, and optimise dispatch from the right warehouse or delivery partner—an area that Goel believes will evolve into a core revenue stream. The company is quietly expanding its fulfilment footprint, but with an AI-first philosophy: “It’s not about adding more space; it’s about placing the right product at the right node before the order even comes.”
Goel emphasises that Shiprocket’s AI shift is not a side project but an organisational reset. Product teams are being restructured, engineers are being retrained, and data infrastructure is being rebuilt to support models that learn continuously.
As India’s e-commerce volumes surge and consumer expectations rise, Shiprocket believes that the logistics winners of the next decade will not be the ones who move the most parcels, but the ones who predict the next move before the parcel even leaves the shelf.
