Teleport moved Southeast Asia's largest air-logistics network to autonomous operations with Shipsy

Teleport moved Southeast Asia’s largest air-logistics network to autonomous operations with Shipsy

Teleport, Southeast Asia’s largest air-logistics network, now saves 20+ hours per week on operations, cut planning time by 75%+, and lifted driver productivity by 20% — all on Shipsy’s unified hub-ops, rider-tracking, and route-optimization stack. Across 164 hubs in APAC and 207 fleets, the system moved Teleport from manual scrambles to autonomous, data-driven execution.

Customer: Teleport. Industry: CEP / air logistics. Region: SEA / APAC (80% coverage across SEA, 164 hubs, 207 fleets). Shipsy modules deployed: Hub Ops App, AI Route Optimization, Real-Time Rider Tracking, E-POD, Unified Order & Rider Dashboard. Headline metric: 20+ hours/week ops savings, 75%+ planning-time reduction, 20% driver productivity increase.

The challenge: scale without the instruments

Teleport runs the largest air-logistics network in Southeast Asia — 80% SEA coverage, 164 hubs across APAC, 207 fleets. As volumes scaled, the operating-system scaled with it the hard way: manual planning, limited rider visibility, and SLA compliance trending the wrong direction.

There was no rider tracking in place, which meant hub managers couldn’t see which riders were where — creating inefficient allocation, delivery delays, and operational blind spots across those 164 hubs. Same-day delivery SLAs were increasingly out of reach. And without centralized tracking, benchmarking 3PL performance — which carriers were meeting their KPIs, which weren’t — was guesswork.

Teleport needed an operating system that could support the scale of its network: real-time visibility on riders, AI-assisted planning, standardized hub ops, and one dashboard for leadership to actually see performance.

The solution: hub-ops + AI routing + rider visibility

Shipsy replaced Teleport’s fragmented tooling with a single dashboard for hub managers that surfaces real-time rider location and status across every hub. Instead of calling drivers to check where they were, hub managers now see the network live.

AI-powered route optimization with automated trip creation became the planning backbone. Trips that previously took planners significant effort to construct are now auto-generated by the system, factoring hub-specific constraints, fleet type, and order mix. Planners shifted from producing trip plans to reviewing and adjusting them — a 75%+ reduction in planning time straight to the bottom line.

Seamless real-time Electronic Proof of Delivery (E-POD) flows back into the backend the moment a delivery completes. No overnight reconciliation; no mismatched status lag. Settlement, customer notifications, and exception workflows all trigger on real E-POD events.

The unified dashboard became the operating lens for order orchestration, rider performance, and weekly business reviews. Leadership and hub managers now review the same data, on the same definitions, across all 164 hubs — enabling real 3PL KPI benchmarking for the first time.

Shipsy’s Hub Ops App standardized in-hub execution: system-driven sorting, scan-based in/out workflows, and clear next-action prompts for hub staff. What used to be tribal knowledge is now encoded in the workflow itself, which makes onboarding new hubs and new staff dramatically faster.

The outcome: 20 hours a week, back

The headline: 20+ hours per week of ops time saved. Those hours came from three places — auto-trip creation replacing manual planning, real-time rider tracking replacing status check-ins, and E-POD automation replacing overnight reconciliation. Hour by hour, the manual scrambles got absorbed into the platform.

Planning time down 75%+. For an operator running 164 hubs, that compounds into meaningful headcount freed. Planners now spend their hours on edge cases, carrier-performance reviews, and network design — not on constructing routine trip plans.

Driver productivity up 20%. Better route plans, real-time allocation, and clearer in-hub workflows mean drivers spend more of their shift on productive delivery time and less on waiting or manual coordination.

Scalable peak-season operations. The same platform that absorbs base volumes absorbs peak volumes — critical for a network that serves e-commerce across SEA during regional mega-sale events.

Together, these outcomes mean Teleport operates at autonomous-ops scale: the platform handles the routine, and the humans handle the judgment calls. That’s the shift from a shipment-visibility tool to a system of action.

What’s next

Teleport continues deepening AI-assisted decision-making across hub and network operations — extending automation into more incident categories, tightening the loop between rider tracking and allocation decisions, and expanding the platform’s role in 3PL benchmarking across its APAC network.