Tech Explained: Here’s a simplified explanation of the latest technology update around Tech Explained: How Allcargo is embedding AI to drive retention and efficiency at scale in Simple Termsand what it means for users..
In global logistics, where margins are thin and volatility is constant, Allcargo Global Logistics, a Mumbai-headquartered global logistics and supply chain company, is betting that the next competitive edge won’t come from scale alone—but from intelligence embedded deep into operations.
For Vaishnav Shetty, the Deputy Managing Director, Allcargo Global, who also serves as chief digital officer at Allcargo Global Logistics, the shift has been deliberate and structural. “What we are driving is a move from reactive sales management to a predictive, data-driven customer strategy,” he says, describing a transformation that is quietly reshaping how the company approaches everything from customer retention to network planning.
Making churn predictable—and preventable
At its global LCL arm, where multiple customers share space in a single container, dubbed ECU Worldwide, the scale is significant—nearly 35,000 active customers every month. In such an environment, even marginal gains can have an outsized impact.
“We treated customer retention not as a commercial metric, but as a strategic lever impacting profitability, network density, and long-term competitiveness,” Shetty says.
To operationalise that thinking, the company built an in-house AI-driven retention engine that analyses millions of transactions across trade lanes, booking patterns, and yield trends. The system flags early warning signals, enabling sales teams to intervene before revenue is lost.
“The idea is to proactively engage customers before revenue leakage occurs,” he explains. “And importantly, we have embedded this intelligence directly into frontline execution.”
The payoff has been tangible: churn reduction of nearly 7% in key markets, alongside improved booking conversions and higher customer participation. But Shetty is quick to emphasise the larger shift. “Predictive analytics is not sitting in a dashboard—it is part of how the business runs.”
Rebuilding the customer interface
If AI is transforming decision-making behind the scenes, platforms like ECU360 are redefining the customer experience.
“Logistics has historically been fragmented and email-driven,” Shetty says. “ECU360 is our effort to simplify and digitise that entire experience.”
The platform integrates quotations, bookings, shipment visibility, and documentation across more than 180 countries and 2,400 trade lanes. But beyond convenience, it serves a deeper purpose.
“By capturing behavioural and transactional data, we are able to improve service predictability, optimise routing, and engage customers more proactively,” he notes. “We see it not just as a booking interface, but as a digital operating layer.”
This shift—from interface to intelligence layer—is central to Allcargo’s broader digital playbook.
Moving AI from pilots to business outcomes
While many enterprises continue to experiment with AI, Allcargo has moved into scaled deployment.
“We moved from experimentation to execution about two years ago,” Shetty says. “Today, AI is a core business function with clear budgets and accountability.”
Across its international supply chain business, AI models are driving churn prediction, pricing intelligence, and sales planning. In express logistics, machine learning is optimising routes and improving capacity utilisation.
“These are not pilots,” he adds. “They are directly influencing revenue quality and customer outcomes.”
The focus now is on expanding AI deeper into workflows and customer-facing processes—with measurable gains in productivity and service quality.
Cloud as the foundation layer
None of this would be possible without a significant overhaul of legacy infrastructure. “A key milestone has been our migration from on-premise systems to a cloud-led architecture,” Shetty says.
The company has transitioned hundreds of servers across regions, enabling faster system integration and real-time visibility into operations. “Leadership teams can now access insights across geographies instantly,” he notes. “That improves decision speed and reduces operational risk.”
Just as importantly, the cloud transition has created the foundation for advanced analytics and AI deployment at scale.
The data challenge across 180 countries
Operating across geographies brings its own complexities—particularly when it comes to data.
“Standardisation is critical,” Shetty says. “Without consistent data structures, you cannot unlock the full potential of AI.”
Through platform-led execution and cloud integration, Allcargo has aligned operational data frameworks across regions. This ensures consistency in service delivery while enabling faster responses to market shifts.
“It’s about maintaining operational discipline at a global scale,” he adds.
Build where it matters, partner where it accelerates
Allcargo’s approach to technology development is deliberately hybrid. “Our preference is to build core strategic capabilities in-house, especially where solutions are tightly linked to logistics workflows,” Shetty explains. “But we actively collaborate with startups and specialists in niche areas.”
This includes partnerships in advanced AI models, document automation, and customer experience innovation. “It allows us to retain control while accelerating innovation cycles,” he says.
Measuring digital beyond cost savings
For Shetty, digital transformation is not an IT initiative—it is a growth strategy. “We evaluate investments through commercial impact, operational efficiency, and risk mitigation,” he says.
AI-led pricing improves conversion rates. Automation reduces manual workload and costs. And better forecasting enhances predictability—a critical advantage in an industry exposed to geopolitical and demand shocks. “Digital transformation is not a cost centre,” he says. “It is a strategic growth driver.”
The harder problem: change
Yet, the technology itself is only part of the equation.“Modernising legacy systems at a global scale is complex,” Shetty admits. “But driving adoption—through training, leadership alignment, and cultural change—is equally challenging.”
Allcargo has approached this as a phased, long-term effort, balancing system upgrades with organisational readiness.
“The key learning is that digital transformation is not a one-time project,” he says. “It is an ongoing capability that organisations must continuously build.”
As supply chains grow more complex and customer expectations rise, logistics players are being forced to rethink their operating models.
For Allcargo, the shift is already underway. Or as Shetty puts it: “The future of logistics will be defined by how intelligently you can predict, adapt, and respond—not just how efficiently you can move goods.”