A Research-Driven
Ai Fitness Companion

FitFam is a UX/UI capstone project developed as part of the UT Austin McCombs School of Business UX/UI Certificate program. The concept explores how an AI-powered fitness companion can help users build consistency in movement by reducing friction and adapting to real-life constraints.

Lead Visual & UX/UI Designer

FitFam was developed by a cross-functional team of six, with all team members contributing across research, ideation, and design. Leveraging my background as a senior visual and graphic designer (and as the most proficient Figma user on the team) I led user flows, wireframing, visual design, and interaction design, shaping the overall UI direction and product experience.

Timeframe/Platform

6 weeks, Mobile first product, using Figma and Figjam to work with teams. The project was framed as a realistic MVP, with decisions guided by usability, scalability, and behavioral insight rather than feature volume.

Our Mission:

To support every fitness journey with smart guidance, positive accountability, and tools that help users build confident, long-lasting habits.

Our Business Goal:

Reach our first 50,000 active users within 12 months through targeted onboarding and partnerships with fitness influencers and communities.

Many fitness apps fail to retain users not because people lack motivation, but because the experience becomes overwhelming or emotionally discouraging. Common problems include:

• Too many features and decisions upfront

• Rigid programs that don’t adapt to daily energy levels

• Progress tracking that feels punitive rather than supportive

• Little personalization at moments when motivation is lowest

From a business standpoint, this leads to low engagement and poor retention. From a user standpoint, it turns fitness into a source of guilt instead of encouragement. FitFam was designed to address this gap by reframing fitness as a flexible, supportive habit, not a performance challenge.

Research began with user surveys and qualitative feedback to understand fitness behaviors, motivation patterns, and friction points within existing fitness apps. The goal was to identify why users struggle to stay consistent and not just what features they use.

User Research & Key Insights

Findings showed that users across fitness levels face similar challenges:

• Difficulty starting workouts due to low motivation or limited time

• Decision fatigue caused by too many options and complex interfaces

• Progress tracking that feels discouraging rather than supportive

• A lack of personalization during low-energy or high-stress moments

These insights highlighted that consistency, not capability, was the primary problem to solve.

Competitive Analysis

To understand how the market currently addresses these challenges, we conducted a competitive analysis of leading fitness and wellness apps. This analysis focused on onboarding, daily engagement patterns, workout discovery, progress feedback, and motivational mechanics.

While many competitors excelled at offering robust content libraries and advanced tracking, several gaps emerged:

• Heavy emphasis on performance metrics over habit-building

• Rigid programs that assume consistent motivation

• Interfaces that feel intimidating or overly prescriptive

• Limited emotional intelligence in guidance and feedback

Opportunity Definition

By synthesizing user research with competitive insights, we identified a clear product opportunity:
A lightweight, adaptive fitness companion that prioritizes encouragement, flexibility and daily context over intensity and complexity.

This directly informed FitFam’s MVP scope, focusing on:

• Ai-guided, conversational entry points

• Short, achievable workout recommendations

• Progress framed around consistency rather than outcomes

To translate research insights into actionable design decisions, we created user personas and empathy maps that represented common motivational states, time constraints, and fitness behaviors.

Rather than focusing on demographics, the personas emphasized contextual factors such as energy level, available time, confidence, and emotional barriers to starting a workout. This ensured the product was designed around how users feel in the moment, not idealized fitness goals.

Empathy maps were used to capture what users think, feel, say, and do when engaging with fitness apps. This process highlighted emotional friction points such as guilt, intimidation, and decision fatigue which reinforces the need for a non-judgmental, adaptable experience.

These artifacts became decision-making tools throughout the project. They informed:

• AI tone and language

• Workout recommendations and constraints

• Progress feedback focused on encouragement rather than pressure

By grounding the design in empathy and behavior, FitFam was shaped to support users realistically, not aspirationally.

FitFam’s information architecture was intentionally kept simple and shallow to minimize cognitive load. The goal was to move users from intent to action as quickly as possible.

Core Structure

• Home / AI Layer: Personalized entry point based on user input
• Workout Content: Short, achievable routines with clear constraints
• Progress & Habits: Lightweight tracking focused on consistency
• Profile & Preferences: Used to personalize recommendations over time

User flows were mapped for key scenarios such as low-motivation entry, time-based workout selection, and post-workout feedback. Each flow was designed to eliminate unnecessary steps and reinforce forward momentum.

With the information architecture and core user flows defined, we moved into wireframing to explore layout, hierarchy, and interaction patterns without the influence of visual styling.

Low-Fidelity Wireframes

• Low-fidelity wireframes were used to quickly test screen structure and flow across key moments in the experience. The focus was on:

• Establishing clear content hierarchy

• Reducing decision fatigue at entry points

• Ensuring primary actions were immediately visible

• Validating that users could move from intent to action with minimal friction

This phase allowed for rapid iteration and refinement, ensuring usability and clarity before committing to visual design.

High-fidelity screens brought validated layouts to life with a polished, product-ready design focused on clarity, consistency, and usability.

Visual Hierarchy & Readability

High-fidelity designs emphasize clear hierarchy and scanability, particularly at moments when users may be low on motivation or short on time. Primary actions are visually distinct, secondary options are de-emphasized, and content is structured to guide users forward without overwhelming them.

• Typography: Clean, highly legible type with clear hierarchy to support scanning and quick decisions

• Color: Soft, neutral tones paired with intentional accent colors to signal progress and encouragement

• Components: Modular cards, buttons, and content blocks designed for reuse and future scalability

Branding decisions directly informed the UI, emphasizing approachability, clarity, and emotional safety. Visual restraint was used deliberately to avoid intimidation or sensory overloa

Viewing and Starting a quick Suggested Workout

User downloads the app → creates a profile → sets up personal attributes, notification/workout/lifestyle preferences, and goals → enables AI companion → lands on the home dashboard.

Responding to a 
Reminder Notification

User receives a reminder (“Ready for your workout today?”) → taps notification options to snooze, dismiss or → app opens directly to today’s suggestion → user starts or schedules it.

Home Screen Ai Chatbot

User opens the app → sees daily chatbot prompt:
“How can I help you feel stronger today?”

User Taps the quick workout suggestion

or User inputs a prompt which draws a suggested workout response from the Ai chatbot.

FitFam shows how research-driven design can lead to a more human, sustainable approach to fitness. By grounding decisions in real user behavior, emotional context, and gaps in the competitive landscape, the product shifts fitness away from rigid performance tracking and toward habits people can actually stick with.

This project reflects my ability to turn insights into clear product direction, build scalable design systems, and deliver cohesive UX/UI solutions that balance empathy with business needs. From research and information architecture to high-fidelity screens and interaction design, FitFam represents a true end-to-end product design process.

If this product were taken forward, the next steps would include usability testing, refining AI tone and personalization, and measuring long-term engagement through habit-focused metrics. Overall, FitFam reflects how I approach product design: thoughtful, user-centered, and grounded in real-world constraints.

Impact

• Clear alignment between research insights and product decisions
• Strong MVP focus without feature bloat
• A cohesive system designed for iteration and growth

Capstone presentation video.

A six minute collaborative walkthrough of the FitFam product, with each team member presenting a portion of the work. I designed and produced the video using Figma assets and Adobe After Effects, defining the visual system, motion, and overall look and feel.