
Context
Users can call this major car manufacturer's emergency service advisors through the vehicles or mobile app. Our team worked on the first internal instant messaging platform. I worked on the end to end experience, design system, visual design, and even participated in technical conversations.
To comply with my non-disclosure agreement, I have omitted and obfuscated confidential information in this case study
My Contribution
Product Design
Visual Design
User Experience
Managing stakeholders
Platforms
Web
The Team
Outcomes
Launched the first internal messaging platform
Created design system for project
Pivoted towards accessibility mid-way
How can we create the first instant messaging platform?
Using my technical knowledge
Emergency advisors work on two monitors. One monitor is for the main emergency service application. The other monitor is for miscellaneous related applications. They needed a way to move the chat window from one screen to the other.
Product Manager originally wanted the chat to be a modal that opens from the emergency service application. However, the modal would be bound to that browser/tab.
I proposed to have the messenger be an independent system that relies on the emergency service application.
Referencing other platforms
I started out with the initial framework by referencing and understanding other instant messaging and customer support chat platforms.

Pivoting our focus based on UX research
Our team reached out to the UX research team to conduct user testing to gather feedback on initial thoughts about an emergency messaging feature.
The research team interviewed 17 participants, and one result stood out to us:
It would be massively beneficial to those who have impaired hearing."
Research Interview Participant
At this point, we decided to change our project focus to:
How can we make emergency services more accessible?
The Emergency Design System
I worked closely with the engineering to create the first chat design system. Here is a snippet of the Figma documentation.







Machine learning will try to predict the sentence as the advisor types based on a list of sentences from the advisor's playbook.
Lists of responses
A quick access list hopes to lessen the cognitive load of remembering what sentences to use.
Impact
ANONYMOUS USER