LiPU

LIPU is a major transportation and logistics provider operating large-scale fleet services across multiple regions. Its business coordinates clients, routes, services, and maintenance across an extensive operational footprint — with high complexity and critical performance dependencies.

LIPU faced fragmented systems and reactive manual processes across its operations. Critical operational data lived in multiple tools with low real-time visibility, causing delays, errors, and increased costs. Maintenance workflows lacked predictability, and operational teams could not proactively anticipate issues — directly impacting fleet availability and service quality.

To address these challenges, our team conducted a deep operational assessment and designed a unified AI-driven intelligence platform that centralizes operational data, decisioning, and execution workflows across fleet management, maintenance, and operations.

The solution delivered a central mobility intelligence core that:

• Centralized operational data across clients, routes, vehicles, and services.
• Orchestrated maintenance workflows from intake to completion with predictive sequencing.
• Embedded machine learning models to anticipate recurring maintenance needs and optimize scheduling.
• Integrated automated virtual agents for real-time workforce interactions.

This enabled LIPU to reduce manual overhead, improve uptime, and operate with predictive operational intelligence.