Carpaal
A community-driven ride-sharing app that makes finding safe, reliable rides simple.
Team:
Sole UX designer
Tools:
Figma, FigJam, Survey Monkey, Slack
Focus:
AI Integration, Safety UX,
End-to-End Mobile Design
Duration:
4 months
Project Overview
Carpaal is a pre-seed startup rethinking ridesharing as a safer, more community-driven alternative. As the sole UX designer, I led the product from research through final UI design.
How Might We:
Transition users from "anonymous strangers" to "verified neighbors"?
Turn chaotic, scattered posts into a searchable, AI-matched system?
Help riders find not just a car, but a compatible community member?
Peer-to-peer ridesharing in the U.S. is fragmented. Many riders rely on informal social media groups that lack safety, trust, and reliability. Existing platforms also tend to feel transactional rather than community-driven.
The Challenge
My Process
I started by aligning with the CEO on Carpaal's business goals, then led the research to define and validate the target audience. From there, I explored riders' pain points and needs by auditing competitors and regional rideshare social media groups, surfacing three key gaps in the current experience.
Key Gaps
The Discovery Gap: Ride info is buried in random threads, making it slow and difficult to find a match.
The Security Void: Anonymous, open-access groups create uncertainty and leave users feeling unsafe.
Transactional Creep: Community-based groups can drift toward profit-seeking services, losing the sense of community that made them appealing.
“I’ve thought about carpooling to save money, but I’m terrified of just getting into a stranger’s car without knowing who they are.”
“The biggest challenge is coordinating schedules. Sometimes people cancel last minute or it’s hard to find someone going to the same place at the same time.”
“I spend more time scrolling through Facebook threads looking for a ride than the actual ride takes. It’s exhausting.”
The Solution
Note: Exact visual design, copy, and branding have been altered to protect Carpaal's confidentiality. Layout, interaction patterns, and feature logic reflect the real product design.
Safety Prioritization
Trust: ID verification, background checks, and user reviews for transparency.
Safety: Gender-specific filtering and AI-powered features: emergency alerts, route deviation detection, and quick check-ins for added security.
Why it matters: Safety and verification were the top concerns for women and first-time riders.
AI Smart Matching
Vibe Matching: Riders match on shared music taste, personality, conversation style, and temperature preference for a more comfortable ride.
Rapport Building: Pre-ride messaging with lighthearted prompts breaks the ice before the trip.
Why it matters: Riding with strangers felt awkward. Letting riders learn about each other beforehand reduces uncertainty, cuts cancellations, and makes the experience feel more natural.
My role: The CEO wanted an AI feature to differentiate Carpaal, but the direction was open. I went back to my research, riders' core fear wasn't logistics, it was getting into a stranger's car. That's what led me to Vibe Matching over a more generic option like route optimization. I defined the matching criteria and designed the rapport-building flow based on pain points from FB rideshare group members.
Outcomes & Impact
To validate the design, I ran usability testing with 20 participants who fit Carpaal's target user profile, using a mix of moderated sessions and a follow-up Survey Monkey questionnaire. The results below reflect that testing.
Increased User Confidence: Testing showed that 40% of participants felt significantly more secure compared to coordinating rides through social media communities, especially due to verification and built-in safety features.
Faster Ride Discovery: Vibe Matching and improved filtering reduced the time needed to find a compatible ride from several minutes of scrolling to under 30 seconds.
Stronger Retention & Trust: The combination of safety features and Vibe Matching increased user comfort and trust by 38%, making riders more likely to complete rides and return for future trips.
Overall, the experience felt less like coordinating with strangers and more like joining a trusted, familiar community, which helped users feel at ease from the very first interaction.
Reflection
I really enjoyed working on this project, as it was such a valuable learning experience for me. Although it was challenging to work in a fast-paced environment at times, it was very exciting and rewarding, and I gained valuable experience collaborating closely with the CEO and developers, learning how to adapt quickly as the product evolved.
The most exciting part of this project for me was getting to work with AI for the first time. I got to explore how AI could be incorporated into the design process, which made me even more curious about the future of design and technology.
One of the biggest things I learned from this project was how much trust and comfort influence the way people use ridesharing apps. Small details, like compatibility cues, pre-ride prompts, and more, helped users feel more at ease. This reiterated how thoughtful design decisions can make digital experiences feel safer, more comfortable, and more human.
Thanks for reading! :)
Thanks for taking the time to explore this project with me! If you’d like to chat more about my process, this project, or anything else you saw along the way, I’d love to hear from you. Feel free to reach out, or continue on to my next case study to see more of my work.