AI Shipment Tracking
Sensos.io
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The Product
This project focuses on expanding air shipment visibility in SYNC by integrating live flight-tracking data from FlightAware’s AeroAPI and AI Predictions.
The goal was to close a critical blind spot in the air segment of the shipment journey, where physical tracking devices go silent mid-flight and carrier data provides only sparse event updates.
The Process
Problem Statement
Tracking Device go offline once airborne
Tracking Device go offline once airborne
Confusion when delays or diversions occurred
Confusion when delays or diversions occurred
Erros are hard to predict & expenisve
Erros are hard to predict & expenisve
Low trust in ETAs and shipment status
Low trust in ETAs and shipment status
“I want a way to track whats the exact location of my shipent while in the air and get notified if there are any anomalies so that I can act on time and prevent issues.”
— Logisitcs Ops. Manager
The Research
Technical Discovery
Competitive Analysis
Input from sales & CS
Findings, Facts & Takeaways
~ 1%
Global shipments move by air
~ 1%
Global shipments move by air
~ 70%
High value goods are shipped by air
~ 70%
High value goods are shipped by air
Live flight position dramatically improves trust
Live flight position dramatically improves trust
Pattern Recognition AI is the goal
Pattern Recognition AI is the goal
Users love ETAs and hisotry events
Users love ETAs and hisotry events
Early alerts are valued by users
Early alerts are valued by users
The Product
Principles
Success Metrics (KPIs)
Feature Adoption
Feature Engagement
In and Outbound Ops Impact
Feature Accuracy
Business Efficiency
Architecture
The solution integrates FlightAware data into SYNC’s shipment lifecycle:
Trigger: User enters an AWB during shipment creation
Matching: Carrier data is used to identify the correct flight in FlightAware
Visualization: Live flight position rendered on SYNC’s existing map and status changes on timeline
Data behavior:
- In-air polling every 3–5 minutes
- On-ground polling every 15 minutes
- Auto-disable after arrival to control costs
Alerts: Key milestones (takeoff, landing) & delays or diversions
Solution Overview
Shipments are automatically matched to flights via AWB and enriched with live flight data directly in the shipment journey. AI pattern recognition enables dynamic ETAs and early delay detection at scale.
Validation & Outcomes
Results
28% ↑
Platform Engagement
28% ↑
Platform Engagement
100% ↓
Tickets of "Where is my Shipment?"
100% ↓
Tickets of "Where is my Shipment?"
Higher trust signals, with users spending more time in the shipment journey during air segments
Increased upsell traction, with air visibility becoming a key driver in enterprise and air-heavy customer deals
API usage remained within forecasted limits, validating the polling and cost-control strategy
The feature also became a strong Sales and demo differentiator, showcasing real-time visibility even when no tracking label was present.
Reflection
This project reinforced the importance of product thinking beyond surface-level UX.
The core challenge wasn’t how to show flight data, but when, why, and at what cost.
Designing this feature required balancing user expectations for “live tracking” against the economic reality of per-call APIs, while still delivering a compelling and differentiated experience. It also highlighted how deeply product decisions shape UX outcomes, often long before pixels are involved.
This is a strong example of translating technical constraints into clear product rules that protect both user trust and business sustainability through AI and automations.
Thankyou :)
“Design is the intermediary between information and understanding.”
- Hans Hofmann
