Service Request Chatbot
Summary
A new AI-powered chatbot product which can classify citizen service requests; ask contextual followup questions; and collect contact details, photos, and location information.
More details and context can be provided in an interview.
Project MetadataMY ROLE
UI/UX Designer
TOOLS
TIMELINE
7 Months
TEAM
CLIENT Daupler
DELIVERABLES Prototypes, Hi-Fi Mockups
GOAL Create a new conversational UI product for citizens to report service requests to their city through the government’s website.
OUTCOME Custom white-label AI ChatBot widget envisioned including 9 input types, onboarding, editing, contextual followup questions, and drafts.
Problem
The current industry standard method for citizens to report service requests are long, complex web forms with many fields and a lot of complex decision making put on the shoulders of the citizen.
Examples of service requests include: water shutoff request, pothole report, new stoplight request.
Solution
Daupler’s core platform (Daupler AI) is a large language model trained on service requests which is able to accurately categorize a reported problem.
I leveraged Daupler AI to create a new industry-first chatbot widget through which citizens can easily report in natural language a description of their service request. The AI is able to categorize the report and then ask contextual followup questions to fill in any needed missing information. Once the problem is fully understood the chatbot gather’s the citizens contact details and, if relevant, the location and photos of the problem.
Introduction
Description Entry
Followup Questions
Phone Entry
Verification Method Selection
Verification Code
Name
Photo Upload
Editing
Drafts
Location Input
Manual Category Picker
Widget Example
Figma Prototype
Demonstrates animations and transition from initial greeting screen to conversation.
Write
Publish
Problem
Research
Analysis
NAME the TYPE
PHOTO HERE
Age range:
How Might We
Include why and who
Ideation
Vision
Design
Solution
Takeaways
Future
Want to learn more?
More Projects
eBooks
Researched, designed, and tested solutions to 3 major UX problems in Amazon's iOS Kindle app. Solved 3 major usability problems for avid readers.
Live Event Tickets
Responsive Web, iOS, Android, PDF. 15% avg. increase in tickets scanned for events.
Live Event Tickets
Built new UI accessible to all 8 vision types.
About COMPANY-HERE
Problem
Outcome
Deliverables
✓ Lorem
✓ Ipsum
✓ Dolor
✓ Lunctum
✓ Vires
✓
✓
Tools Used
✦ Lorem
✦ Ipsum
✦ Lunctum