Soham ChokshiCo-Founder & CEO

Since 2020, we have faced a continuous series of supply chain crises. It began with the COVID-19 pandemic, followed by global chip shortages, the Russia-Ukraine war, tensions in the Red Sea, and broader conflicts in West Asia.

Geopolitical events are forcing ships to reroute, such as going around the Cape of Good Hope, which adds about 14 days of transit time. For thin-margin commodities, this rerouting can add roughly 30% in extra costs.

The constant uncertainty has shown companies that they cannot rely on a single source or path. To build resilience, enterprises are investing in alternate suppliers, contracting with multiple shipping lines, and leveraging technology to handle unexpected disruptions.

In transportation economies like Australia that rely heavily on diesel, prices have surged by nearly 80%. This massive cost increase is not something carriers can easily adjust to, forcing them to find technological efficiencies to survive.

New regulations now mandate that if a transportation company charges a customer extra fees, such as fuel surcharges, they must pass those funds on to the drivers in a fair and transparent manner.

As shipment volumes grow, the labor force cannot scale proportionally. In major markets like Europe, Australia, and the US, there simply are not enough drivers and logistics workers to handle the manual workload as it increases.

Due to changing customer demands and the influx of affordable manufacturing goods, purchase lot sizes are decreasing. This means the overall number of individual shipments is increasing dramatically, creating much higher transaction volumes.

Rather than operating in isolation, AI can take over repetitive manual tasks, allowing human workers to focus on complex decisions. This amplification increases operational efficiency and helps humans manage larger shipment volumes.

Shipsy has processed over 400 million shipments, creating a massive database mapping addresses to exact coordinates. We use AI agents to clean up unclear address formatting and automatically clarify details with customers before delivery.

Improving address formatting and precision mapping has a direct impact on the bottom line. Accurate coordinates prevent failed deliveries and optimization errors, saving companies between 8% and 12% in operational costs.

Instead of sending a driver for every single order, AI analyzes incoming orders in real-time. If a second order from the same neighborhood or building comes in within a few minutes, the system batches them together, reducing the delivery cost per order.

We enforce a strict constraint where every AI agent must report to a human. AI is not permitted to operate in isolation. The human in the loop must make the final call on payouts, financial decisions, or customer order cancellations.

Layering isolated AI agents on top of broken systems does not solve the root problem. The future requires intelligent, integrated orchestration systems that help humans make better decisions and drive actual business outcomes.