Carely · AI-Assisted Telehealth · Case Study
750
Component
Timeline
May – June 2026
Type
Self-initiated
Role
UI/UX Designer (solo)
Carely
Making telehealth feel more prepared, personal, and less manual.
I redesigned two high-friction moments in the patient journey, finding the right provider and preparing for a consultation, using conversational AI to reduce effort while keeping patients informed and in control.

Project Overview

Carely is a telehealth platform connecting patients with doctors and therapists for on-demand consultations.

I focused on two key moments in the patient journey: finding the right provider and preparing for a consultation. I redesigned both experiences as AI-assisted flows, exploring how conversational AI could reduce manual effort, gather more useful context, and help patients feel more prepared before connecting with a provider.

My Role

I worked as one of three product designers on an NDA'd telehealth app. The AI-assisted discovery and check-in shown in this case study are my own, designed independently on top of it.

Find care screen Finding your match loading screen Your AI Matches screen
Carely flow screen 1 Carely flow screen 2 Carely flow screen 3 Carely flow screen 4 Carely flow screen 5 Carely flow screen 6 Carely flow screen 7 Carely flow screen 8 Carely flow screen 9 Carely flow screen 10 Carely flow screen 11 Carely flow screen 12 Carely flow screen 13 Carely flow screen 1 Carely flow screen 2 Carely flow screen 3 Carely flow screen 4 Carely flow screen 5 Carely flow screen 6 Carely flow screen 7 Carely flow screen 8 Carely flow screen 9 Carely flow screen 10 Carely flow screen 11 Carely flow screen 12 Carely flow screen 13
Hand holding phone with Carely app

Research Plan

How I built a data-driven product

Research Plan Published Research User Feedback Competitive Analysis Context 1 Product Context 4+ Telehealth / AI products analyzed 150+ User reviews analyzed 10+ Academic studies / papers reviewed
Main Insight from Research

Patients want less friction when finding a provider and preparing for a consultation. Conversational AI can help, but it needs to remain transparent and optional.

Persona: Laurie, everyday patient Empathy map for Laurie

Persona & Empathy Map

Using insights from competitive research and published studies, I developed a persona and empathy map to represent the target audience.

Final Deliverables

I designed:

AI Discovery
+
AI Check-in
+
Doctor Handoff Brief

Visual Style

Typography
Aa
Plus Jakarta Sans · Light, Regular, Medium, SemiBold
Heading H1SemiBold24px / 32px
Heading H2SemiBold20px / 28px
BodyRegular14px / 20px
LabelMedium12px / 16px
Brand Colors
#FAFAFA
#6366F1
#FF5A3C
consultant-details-card component top-consultant-card component text-field component icons component button component

Feature Decisions

Five choices about how the AI shows up, asks, listens, and hands off, made from what the research kept surfacing.

01

Always tell people it's AI

People trust AI health tools more when the AI is upfront about being AI and explains itself clearly, not just when it happens to be accurate.

02

Typing is always an option

Not everyone wants to talk out loud about a health problem, so I let people type their answers instead of forcing them to use voice.

03

Patient approves it before it's sent

Most AI health chatbots don't clearly tell you when you're talking to AI instead of a real doctor, so before anything gets sent to the doctor, the patient has to look it over and approve it first.

04

Let the patient finish talking

Doctors interrupt patients after about 11 seconds on average, so I built a screen where the patient can fully explain what's wrong without anyone cutting them off.

05

Confirm the doctor actually read it

Patients often have no idea if their doctor actually read what they sent in before the appointment, so I added a screen that tells the patient "yes, your doctor read this" once they have.

What this design targets
11s → no cutoff
average time before a doctor interrupts, vs. as long as the patient needs
100%
of AI moments labeled clearly as AI

Finding a provider: browse, or get matched

Find Consultant is the standard way in, browse and filter by category. Once a patient describes what's going on, Your AI Matches shows up instead, ranked and explained.

Browse by Category
Find Consultant screen, manual browse and search
The standard entry point, browse and filter by category
AI Matches
Your AI Matches screen, showing ranked providers with match reasons
Shown once the patient describes the problem, ranked with the reason why

Explaining what's wrong: on the paid clock, or before it

Audio and video consultations bill per minute from the moment they connect, so explaining symptoms out loud eats into paid time. The AI check-in captures all of that first, for free, before the clock starts.

During the Paid Call
Doctor booking screen showing per-minute pricing for audio, video, and chat
The paid clock starts before you've explained anything
AI Check-in First
Voice check-in screen where the patient talks freely before the call
Patients say everything here, untimed and unbilled

Supporting Screens

A few more screens to round out the picture, the rest of the app is under NDA.

Figma screens library: full set of screens organized by flow, onboarding, home, profile, consultant, calls, wallet, messaging, live events, and AI discovery
Doctor profile screen with intro video and services Provider onboarding, setting expertise, schedule, and per-minute pricing Live video consultation screen Consultant availability modal

Reflection

Reflection note: Good AI UX is about boundaries. The most important design decisions were not about what the AI could do, but where it should stop, when it should ask, and when the patient should take over.