AI Predictions Transform Transportation & Logistics

Time sensitive shipments needed to get from shipper to airport quickly in order to meet delivery SLAs, and unplanned pickups often derailed planned delivery plans and increased operational costs. Learn how ML and logistics AI helped planners understand trends and increase their ability to plan around anticipated pickup requests.

GeminiBigQueryStreamlitGoogle Cloud Platform (GCP)Artificial IntelligenceCase Study

Insights from Sparq

april 01, 2025 — 2 minute read

Challenge: Unpredictable Pickups Hurt Efficiency

A global transportation & logistics provider couldn’t accurately forecast pickup volumes for its highest service level air delivery service. Planners relied on intuition, risking:

Over-allocation of trucks, inflating fuel and labor costs

Under-allocation, causing delays and unhappy customers

Fragmented data, limiting scalability and performance

They needed a transportation software development partner to inject data-driven insights into daily operations.

Solution: Logistics AI for Smarter Dispatch Planning

Sparq deployed an agile, AI-driven approach:

Machine Learning Forecasting: Built a GCP Gemini model to predict pickup volumes using historical data and route patterns

Probability Modeling: Forecasted expected quantities by day and region

Interactive Dashboard: Delivered a Streamlit interface for real-time planner insights

Scalable Infrastructure: Leveraged BigQuery for high-performance, future-proof data processing

Results: Cost Savings, Accuracy, and Future-Ready AI

Improved Forecast Accuracy: Reduced planning errors and boosted route efficiency

Fuel & Time Savings: Optimized truck allocation, lowering costs and emissions

Sustainability Gains: Contributed to corporate carbon reduction targets

Enterprise AI Foundation: Created a reference architecture for future logistics AI projects across GCP