AI Agentification
Logistics Tech Co.

A major logistics enterprise was grappling with high operational costs and inefficiencies due to over 1,000 operators manually tracking trucks, updating statuses, and coordinating delivery events. The manual effort resulted in delayed turnarounds, tracking errors, and limited scalability.

To address this, we initiated a 2-week field study, closely observing on-ground workflows of operators, supervisors, and dispatchers. This research helped identify repetitive patterns, bottlenecks, and automation-ready tasks.

We then developed rapid AI prototypes for critical workflows—truck tracking, route updates, delivery confirmations—gathering early feedback to refine solutions.

Collaborating with internal engineering teams, we mapped existing systems and APIs to ensure smooth backend integration. With this foundation, we designed and deployed a suite of AI agents, each tailored to a specific workflow—real-time tracking, alerting, document verification, escalation handling, etc.

Deployment was done in phases, allowing teams to adapt gradually while we measured impact and optimized the systems in real-time. We also created a long-term Agent Roadmap, enabling seamless scaling across departments like fleet, warehousing, and dispatch.

Impact:

• AI-powered Control Tower operational with 8+ intelligent agents

• Automated 70%+ of manual truck tracking tasks

• Enhanced delivery accuracy and reduced turnaround time

• Created a framework for continuous agent ecosystem evolution

This project laid the foundation for full-scale AI-driven operations within the company, unlocking efficiency and agility at enterprise scale.