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Overview

EVR is a concept UX/UI project for a SaaS platform that supports operations teams in managing electric vehicle charging efficiently across large organizations. It explores how digital tools can help reduce energy costs, improve infrastructure usage, and support better decision-making at scale.

I chose this project as part of my portfolio because I wanted to challenge myself with a domain that involves operational complexity, data-heavy decision-making, and system-level thinking.

 

This project explores how UX design can simplify complexity, provide actionable insights, and support smarter decision-making through intuitive dashboards and AI-powered recommendations.

Market and Target Audience

  • Companies with large electric vehicle fleets

  • Operations and facility managers responsible for EV charging

  • Organizations facing rising electricity costs and charging inefficiencies

Problem Statement
Managing EV charging at scale is complex, requiring real-time monitoring of station availability, power consumption, and ongoing maintenance.
  • Electricity demand fluctuates throughout the day. Without smart load balancing, peak usage can lead to excessive costs and inefficient power distribution
  • Dynamic electricity tariffs offer cost-saving opportunities, but operators often lack the tools needed to effectively optimize charging schedules
  • Managers are already juggling multiple responsibilities. Without the support of data analytics and AI-driven insights, making timely and efficient decisions becomes nearly impossible
Benchmark Analysis

Competitive Landscape of EV Charging Management Platforms

I compared three key platforms offering EV Charging Management Systems (CSMS) as SaaS solutions. Each platform brings a unique strength—GreenFlux scales, Driivz analyzes, ChargeLab simplifies—but all leave room for UX and personalization improvements.

SWOT
User Research
Personas

To better understand the challenges of managing EV charging at scale, I interviewed facility and operations managers responsible for parking lots, buildings, and energy systems. After interviewing the selected managers, I built three personas to help me further characterize the product.

Persona 1

Michal Levi

Operations Manager, Ramat Aviv Mall

 

Oversees daily operations, including parking lot maintenance and EV charging station functionality.

Persona 2

David Cohen

VP of Operations, Migdal Insurance.

Responsible for managing multiple buildings, including electrical infrastructure and EV charging logistics.

Persona 3

Yossi Biton

Operations Manager, Property management Firm

Leads maintenance for a portfolio of high-rise buildings, coordinates service teams, and oversees energy efficiency initiatives.

You are invited to get to know them a little more in depth:

Empaty Maps

To better understand our users' experiences, I created empathy maps for each persona. This tool helped me capture what users see, hear, think, feel, say, and do in their daily work, allowing me to uncover hidden frustrations and emotional drivers that guided the design decisions.

User Journy

To characterize the User journey, I chose to continue with one persona: David Cohen.
David has the greatest responsibility: on the one hand, the free charging service is a benefit given to the company's employees, on the other hand, he must be careful not to exceed a budget defined by the company he works for.

I chose a common scenario from David's daily life: a new employee starts working at the company. David needs to add her as a user of the system, find her a charging station that will not burden electricity costs but will also be accessible to her when she needs it, set up alerts for the new employee, and in general, monitor and report to management once a quarter.

HMW
How might we support David in making faster, data-driven decisions about EV charging performance and energy costs?
User Flow Chart

I chose a common scenario from David's daily life: a new employee starts working at the company. David needs to add her as a user of the system, find her a charging station that will not burden electricity costs but will also be accessible to her when she needs it, set up alerts for the new employee, and in general, monitor and report to management once a quarter. This flow ensures new employee setup is efficient and monitored.

user flow chart
Prototyping
Design Principles
Early Layout Exploration

During the screen design process for David, I focused on aligning each layout with the needs identified in the customer journey. The goal was to make key information — especially KPIs — instantly accessible and easy to understand. In every screen, I integrated AI-powered insights to help David quickly discover trends, understand usage patterns, and take informed action with confidence.

UX wireframe.png
system architecture

This system architecture diagram maps the EVR platform modules by user persona, feature scope, and external integrations. At this stage, only David's dashboard and related components were fully designed. The structure lays a clear foundation for expanding future modules for additional personas (Michal and Yossi), as shown at the top.

System Architecture Map.png
UXI Design

This section showcases selected interface designs from the EVR platform. Each screen was crafted to support operational decision-making through data clarity, smart visualizations, and contextual AI insights.

 

The design emphasizes simplicity, speed, and scalability—ensuring that users like David can quickly understand key metrics, take action, and maintain efficient control over their EV charging infrastructure.

Design System
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Reflection On The Project

When I started working on this project, I knew very little about EV infrastructure. But curiosity (and a lot of user simulation via ChatGPT) helped me dive deep into the world of operations managers like David, Michal, and Yossi.

As I designed the system, I regularly shared it with colleagues from the industry. Their feedback helped me challenge assumptions, simplify complex flows, and fine-tune the dashboard to better support decision-making.

Key lessons:

  • Users don’t need more data - they need clarity: That’s why I focused on actionable insights, smart prioritization, and clean visual hierarchy.

  • Still learning, still iterating: Even though this is a case study, I keep refining it. Every new tool I discover - like Genway, an AI tool for simulating user interviews-  makes me want to test assumptions and push the research further.

  • Making complex systems feel approachable: Working on this project gave me the clarity (and confidence) that I truly enjoy designing for complex products — translating operational logic into tools that support clear, timely decisions. It's the kind of challenge I want to keep exploring.

 

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