Transportation • AI-Driven optimization

Revolutionizing fleet management with AI innovation

iOS Native App

Android Native App

Tablet App

Desktop App

Summary

Redesigning a fleet management platform to streamline workflows, integrate AI-driven decision-making, and enhance user experience for fleet managers and operators.

Skills

• User research
• Wireframing
• UX/UI design
• Prototyping
• Interaction design
• Product design
• Accessibility (WCAG)

Development Team

• 8 Product owners
• 28 developers
• 1 Data analyst
• 4 QA engeneers
• Design team lead
• UX researcher
• 3 designers

Role

Senior Product designer

What?

Transforming fleet management with AI-powered efficiency

The fleet management platform had grown over 18 years, accumulating outdated, inconsistent UI patterns and fragmented workflows. Navigating its complex features—fuel tracking, route optimization, and driver analytics—was inefficient, slowing down decision-making for fleet managers.

This redesign focused on unifying the interface, integrating AI-driven insights, and optimizing workflows, ensuring a seamless, data-driven experience for modern fleet operations.

Why?

The problem we are solving

Fleet managers struggled with slow workflows, lack of predictive insights, and an aging interface that made daily operations inefficient. Research and data analysis uncovered key pain points:

Inefficient route & Fuel planning

73% of fleet managers relied on manual fuel station selection, leading to unnecessary detours and higher fuel costs.

Cumbersome workflows

21% of operations were slowed down due to inconsistent navigation and fragmented workflows — requiring up to 7 clicks for basic fleet tasks.

Limited fleet AI

31% of managers lacked real-time driver behavior insights, making it difficult to detect risky driving patterns, optimize fuel usage, and improve fleet performance.

“

Managing a fleet shouldn’t feel like a guessing game — I need real-time insights and a system that works with me, not against me.

— Andris, 42, Fleet Manager

Who we built this for?

Our target users

The redesign focused on two key user groups:

🚛 Fleet Managers & Operations Leaders → Responsible for optimizing routes, managing fuel costs, and ensuring driver efficiency. They needed AI-driven insights, real-time data, and streamlined workflows to make faster, more informed decisions.
👨‍🔧 Fleet Drivers & On-Ground Operators → Execute daily routes and rely on accurate navigation, fuel station recommendations, and safety monitoring. A simplified, intuitive interface helped them reduce detours, improve compliance, and minimize fuel wastage.

By addressing these users’ needs, we built a more efficient, intelligent, and scalable fleet management experience. Pain points were analyzed not only through a user lens but also through their impact on cost, operational delays, and long-term scalability — bridging user needs with business priorities.

Was it more than just UX?

Where product thinking meets impact

In a complex ecosystem with eight product owners, I took a lead role in translating fragmented product vision into actionable, outcome-focused design. Working with three of the owners, I tied design decisions directly to operational KPIs — fuel cost reduction, route efficiency, and real-time decision support. Design here wasn’t polish — it was performance infrastructure.

How?

My approach

Redesigning an 18-year-old platform meant modernizing without breaking what worked. I focused on incremental improvements — integrating AI automation, streamlining navigation, and simplifying key workflows.

By collaborating closely with fleet managers and engineers, we shaped solutions around real-world use. Iterative testing helped us validate usability while aligning AI features to support cost reduction and faster decision-making.

Insights

User research

Conducted research in collaboration with a UX researcher, gathering insights from fleet managers and operators to identify workflow bottlenecks.

Structure

Optimized workflow

Streamlined workflows with an intuitive task flow and a well-structured information hierarchy. Below are examples of improvements in the Fuel Locator and Fuel Comparison flows.

Refining through user feedback

Iterative prototyping & Testing

The Quick Fuel station comparison tool is an example of how we solved key challenges by allowing fleet managers to evaluate and compare gas stations based on convenience and cost. This streamlined route planning and fuel efficiency, enabling better decision-making.

Through interactive prototypes, we validated solutions with real users, refining the design based on feedback to ensure an intuitive and effective experience.

Consistency

Scalable Design system

Implemented a structured grid system as part of a broader design system overhaul. This included recreating and improving components, enhancing the font library, and refining accessibility to align with WCAG standards, ensuring a consistent, scalable, and inclusive experience across platforms.

Mobile experience

Enhancing fleet management on mobile

In addition to the web platform, I played a key role in redesigning the fleet management mobile app to ensure a seamless, on-the-go experience for fleet managers and drivers. My focus was on simplifying navigation, improving usability, and optimizing key workflows for mobile use.

Design outcome

Final reslult

The redesign introduced key enhancements that streamlined workflows, improved accessibility, and enhanced decision-making for fleet managers. Below are before-and-after example showcasing how these improvements transformed the Fuel summary:

✔ Replaced static tables with real-time fuel consumption insights.
✔ Tracked idling, acceleration, and fuel-wasting patterns.
✔ Enabled predictive fuel efficiency tracking for cost savings.

Delivered value

🚀 Tangible impact

My contributions helped streamline workflows, enhance usability, and integrate AI-driven analytics — directly improving decision-making for fleet managers. The following key metrics highlight the success of our user-centered, business-aligned approach:

Each UX improvement was intentionally mapped to a business outcome — whether reducing manual reporting, accelerating data interpretation, or enabling smarter route planning.

Faster data
interpretation

Replacing tables with a dashboard reduced time spent analyzing fuel consumption and driver behavior.

Reduction in
manual reporting

Automated analytics minimized reliance on manual fuel tracking, saving fleet managers valuable time.

Improved fuel
efficiency

Updated dashboard insights helped fleet managers optimize refueling strategies and reduce unnecessary fuel waste.