Gutsy

Living with a chronic illness means paying attention to a thousand little signals. Gutsy uses AI to help them make sense.

Overview

Gutsy explores how AI, health tracking, and conversational support could help people living with chronic digestive disorders make sense of the factors affecting how they feel.

my role

Sole Creator:
UX & Product Design
UX Research
Visual Design
Illustration & Data Visualization

team

Independent project

timeline

13 months

platform

Mobile App

tools

Figma
Adobe Creative Cloud
Pen & paper
Zoom

deliverables

Research
Design system
Interactive prototype
Case study

the product

Meet Gutsy.

Explore the interactive prototype, or continue through the story below.

Jump to Prototype
Essential Flows

the challenge

Managing a chronic condition means keeping track of an overwhelming number of factors.

Symptoms, food, sleep, stress, medication, and other factors can interact in ways that are difficult to recognize day to day.

How might we help people with chronic digestive conditions track the factors affecting their health and recognize meaningful patterns?

DISCOVERY

Understanding
life with an
invisible illness.

Research and conversations revealed a problem larger than symptom tracking: making sense of what the body was telling them.

RESEARCH

Mapping the complexity.

I made the following infographic to map out my research and understand visually the scale of chronic digestive disorders and how symptoms, behaviors, and everyday circumstances intersect.

USER CONVERSATIONS

Six conversations revealed how difficult it is to connect everyday choices with how you feel.

Participants described tracking symptoms, food, sleep, stress, and other factors across disconnected tools (or simply trying to remember them). The opportunity lay in connecting what the they were already experiencing.

01

TOO MUCH TO TRACK

Information overload

Keeping track of everything affecting how I feel can become another task in itself.

KEY INSIGHT

Health information is scattered across symptoms, food, sleep, medication, stress, and daily routines.

02

PATTERNS ARE HARD TO SEE

Delayed cause & affect

Sometimes I know something made me feel worse, but I don't know what it was.

KEY INSIGHT

Symptoms may appear long after a choice or behavior, making cause and effect difficult to recognize.

03

DATA NEEDS CONTEXT

Knowing what matters

I can record what happened, but that doesn't necessarily tell me why it happened.

KEY INSIGHT

Logging alone isn't enough. People need help turning scattered information into meaningful patterns.

THE HIDDEN BURDEN

Managing your health often becomes another source of stress.

People were already navigating pain, fatigue, unpredictable symptoms, and disrupted routines. Tracking it all could become another task on an already difficult day.

What patterns revealed

Tracking symptoms alone didn't make living with chronic illness any easier.

People weren't struggling to collect health information as much as understand what it meant. Three principles shaped the design:

01

REDUCE THE 
BURDEN

Make logging simple enough to fit into daily life (not become another health-related task).

02

CONNECT WHAT 
MATTERS

Bring symptoms, food, sleep, stress, and other factors together so relationships can emerge over time.

03

SUPPORT, DON'T 
DIAGNOSE

Use AI to help people understand their health information while maintaining medical guidance.

MEETing THE USER

Chronic illness doesn't stop when everyday life gets busy.

Our representative user has to balance chronic illness with an already demanding life.

competitor audit

Existing health tools capture data, but rarely connect the whole story.

I evaluated health tracking, symptom logging, nutrition, and patient-management apps. Most handled one part of the experience well, but few connected symptoms, food, sleep, stress, medication, and other factors into meaningful patterns.

Experience Synthesis

Mapping the emotional journey revealed where support mattered most.

I mapped my user’s day to identify where symptoms, uncertainty, and the effort of managing her health created the most friction (and where a product could meaningfully help).

Managing Brenda’s condition wasn’t one task, but dozens of small decisions competing with the rest of her life.

Design evolution

Turning health data into something people could actually use.

Early concepts explored how tracking, visualization, and AI assistance could work together without adding to the burden of managing a chronic condition.

Design Goals

LOW 
EFFORT

Make tracking quick enough to fit into everyday life.

MAKE 
CONNECTIONS

Turn scattered health data into patterns people can recognize.

BUILD 
TRUST

Keep AI assistance understandable, supportive, and within clear boundaries.

outside the box

What if the solution were something other than a mobile app?

Before settling on mobile, I explored wearables and AR as lower-friction ways to capture information and surface guidance in context. Smart rings and glasses expanded what the experience could become, but also clarified where it needed to begin.

early exploration

How could complex health information become understandable?

I explored ways to visualize relationships across symptoms, behaviors, and time, looking for patterns that could be understood at a glance.

visualizing the invisible

Could the biology of CDDs become part of the experience?

Being that antibodies, bacteria, immune responses, and the microbiome are tied directly to CDDs, I imagined these biological features as characters, looking for a visual language that could make complex biology more approachable without trivializing it.

narrowing the field

The best solution needed to fit into life, not ask life to fit around it.

I compared the concepts against the needs uncovered in research: low effort, meaningful insight, accessibility, and trust. Wearables and connected devices offered potential, but required greater cost, adoption, and behavior change. A mobile experience offered the strongest place to start using technology people already had.

early flows

With the platform defined, I began shaping the experience.

I mapped how users could quickly capture symptoms, food, and other health factors, then connect that information over time. Early flows explored check-ins, dashboards, conversational guidance, and pattern recognition.

design principles

Three principles guided every decision that followed.

As the mobile experience took shape, I used three principles to keep it grounded in what I learned from research: meet people where they already are, minimize the effort required to participate, and earn trust before asking users to rely on intelligent guidance.

01

EVERYDAY
ACCESS

  • Use technology people already have
  • Available wherever users are
  • Easy to return to throughout the day

NEW DIRECTION

Meet people where they already are.

02

LOW 
EFFORT

  • Chronic illness already demands attention
  • Repeated logging creates fatigue
  • Complex inputs discourage consistency

NEW DIRECTION

Make participation easier than remembering everything.

03

EARNED
TRUST

  • Health information is deeply personal
  • Insights need to be understandable
  • Users need control over their information

NEW DIRECTION

Make intelligent guidance transparent, supportive, and clearly bounded.

Convergence

The experience began taking shape around everyday life.

Wearables, smart-home devices, and robotics expanded what Gutsy could eventually become. But the research pointed toward a simpler place to start: a mobile experience that could bring fragmented health information together without asking people to adopt another device or routine.

the foundation

Start with a phone, and build an ecosystem around it.

Choosing mobile gave Gutsy a practical foundation for tracking symptoms, recognizing patterns, and providing intelligent support today, while leaving room for connected devices and new forms of interaction in the future.

practical & familiar

How a mobile app provided the right foundation:

  • Available whenever symptoms happen
  • Quick enough for everyday tracking
  • Personal enough to recognize patterns over time
  • Flexible enough to connect with future devices
  • Familiar, with little to no learning curve

shaping the experience

With the platform settled, I began turning complex health needs into a simpler daily rhythm.

With mobile established as the foundation, I sketched ways to bring symptoms, food, medication, mood, and other health signals into one manageable experience. Early wireframes explored faster logging, clearer patterns, trigger identification, and support.

Core user flow

Managing health as a habit.

Each step connects everyday inputs into patterns and personalized support.

01
Check In
Log how you're feeling with a quick daily check-in.
02
Add Context
Capture symptoms, food, medications, stress, hydration, sleep, and other relevant factors.
03
Recognize Patterns
See connections across health data that are difficult to notice day to day.
04
Get Support
Receive personalized insights, recommendations, and AI-assisted guidance.
05
Take Action
Use what you’ve learned to make informed choices and communicate more clearly with your care team.

logging & understanding

Making a complicated task feel simple.

Chronic illness demands constant attention. As the wireframes evolved, I looked for ways to shorten routine tasks, keep optional details truly optional, and make information collected over time more useful without asking more from the user.

01

QUICK 
CHECK-IN

Give users an immediate view of the health information that's most important.

02

FLEXIBLE
LOGGING

Offer multiple ways to log, including text, voice, and widgets, so users can choose what works in the moment.

03

FAMILIAR
CONVERSATION

Bring entries together over time to reveal connections that can be difficult to recognize day to day.

04

IDENTIFY 
TRIGGERS

Connect food, hydration, symptoms, and other factors to help users recognize possible triggers.

interaction system

After multiple iterations, AI became the connective tissue of the experience.

Gutsy needed to bring symptoms, food, medication, stress, sleep, and other daily factors into one connected experience. AI offered a way to recognize patterns across that information while also giving users a familiar, conversational way to interact with it.

design language

I sketched out a visual language that could make health management feel less medical, and more human.

As the app evolved, I explored increasingly expressive directions for Gutsy, testing color, interface density, navigation, typography, and personality along the way. Gradually, those pieces came together into an energetic visual system that made complex health information feel clearer, friendlier, and more approachable.

sketching out the companion

What should support actually feel like?

I wanted Gutsy to provide more than intelligent guidance. It also needed to feel supportive. To give that idea a face, I explored robots, pets, abstract characters, and increasingly anatomical forms. The direction gradually movedaway from something technological or overly sentimental toward a companion that felt warm, expressive, friendly, and unmistakably connected to gut health.

the mascot emerges

Gutsy needed a personality flexible enough to support people in very different moments.

With AI at the heart of the experience, I used it to help translate my character sketches into a consistent mascot system. Through many iterations, Gutsy developed into a companion that could be encouraging, playful, reassuring, or informative depending on the moment.

A consistent character turns everyday tracking into an ongoing relationship, making routine interactions feel more personal and encouraging.

User validation

Could Gutsy make managing health feel less like work?

Now it was time to see whether the experience could actually help. I put Gutsy in front of users to learn whether quick logging, pattern recognition, and conversational guidance could make everyday health management feel clearer and more manageable.

first impressions

The app's value became evident when scattered information became connected.

Users responded strongly to Gutsy’s visual design and personality, as well as its ability to bring symptoms, meals, medication, stress, and other daily factors together. Some found the amount of information overwhelming, which led me to explore a darker, calmer interface with less visual strain. More importantly, the feedback reinforced Gutsy’s central opportunity: not simply tracking health, but helping people understand what their data might mean.

The experience shouldn’t ask sick people to work harder in order to understand their health.

gutsy in practice

A motivating health companion with a conversational interface.

The final experience brings everything together around one principle: make capturing what matters effortless, then turn it into information people can actually use.

when talking isn't an option

At work, in public, or anywhere privacy matters, the same conversational check-in works through text.

clarity in context

Quick entries become a continuous health record, helping users follow changes over time and turn scattered information into something they can understand and act on.

health isn't only data

Community creates space for another kind of support: learning from people navigating similar conditions, challenges, and questions.

the right input
for the right moment

There’s no single easiest way to log. Speak when it’s natural, text when privacy matters, or use Widgets when time and energy are limited. All contribute to the same health picture.

interactive prototype

Experience Gutsy for yourself.

Explore how Gutsy turns everyday check-ins into a clearer picture of your health, connecting symptoms, habits, and patterns over time.

next steps

Turning insight into something people can trust.

Gutsy’s next challenge involves proving that the patterns it surfaces are reliable, understandable, and useful enough to inform everyday health decisions.

Final reflection

The biggest challenge was  making data meaningful.

The opportunity was not to make people track more, but to help them understand the life they were already living.

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