Available on App Store
PeakMacro
A calorie-tracking AI app designed to make nutrition tracking smarter, simpler, and more personalized.
TIMELINE
2025-Present
PLATFORM
IOS App
Website-Peakmacro.com
ROLE
Founding Designer
TOOLS
Figma, Adobe, Lucid chart, Microsoft word
Overview
Making nutrition tracking as easy as describing your meal while tracking habits over time.
THE CHALLENGE
Existing nutrition apps like MyFitnessPal require users to search through massive food databases, scan barcodes, and log each ingredient individually a process that takes 10+ taps per meal. This friction causes 60% of users to abandon tracking within two weeks.
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Beyond logging, most apps fail to provide meaningful insights. Users can input data, but rarely receive personalized macro breakdowns, habit patterns, or actionable feedback that drives long-term behavior change.
THE SOLUTION
PeakMacro uses AI to understand any way you describe food from “chicken and rice” to “185g chicken breast, 250g jasmine rice, 30g almonds.” Snap a photo or type a few words. The more detail you add, the more accurate the result
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Tracks daily and long-term nutrition habits
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Saves favorite meals and frequently eaten foods for one-tap logging
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Delivers detailed macro insights (protein, carbs, fats, fiber, micronutrients)
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Identifies patterns over time and provides personalized nutrition feed
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Habit tracker
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MY ROLE
​As founding designer, I owned the end-to-end design process from user research and persona development to information architecture, a comprehensive design system with 140+ trackable metrics, and the complete UI for the iOS application.
RESEARCH
Understanding the landscape
I conducted competitive analysis, user interviews, and persona development to uncover the gaps in existing nutrition tracking and design for real human behavior.
COMPETITIVE ANALYSIS
My FitnessPal
STRENGTHS
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Massive food database
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Barcode scanning
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Social features
WEAKNESS
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Cluttered UI
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10+ taps to log a meal
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No food quality tracking
OPPORTUNITY
Users want speed over exhaustive databases
Cronometer
STRENGTHS
WEAKNESS
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Micronutrient detail
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Accuracy-focused
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Clinical integrations
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Steep learning curve
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Intimidating for beginners
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No AI assistance
OPPORTUNITY
Precision without complexity gap
Lose it
STRENGTHS
WEAKNESS
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Simple interface
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Goal-oriented
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Photo logging
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Limited macro detail
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Gamification feels shallow
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No food categorization
OPPORTUNITY
Simplicity + depth is underserved
Carbon diet coach
STRENGTHS
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Adaptive algorithms
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Coach-like experience
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Auto-adjusting macros
WEAKNESS
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Expensive subscription
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No free tier
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Complex onboarding
OPPORTUNITY
AI coaching at accessible price points
Key Findings
Every competitor forces users into a database-first workflow — search → select → adjust portions → confirm. This creates a 10+ tap process per food item.
PeakMacro's opportunity: use AI-powered natural language parsing to reduce meal logging to a single free-text input, cutting interaction time by ~80%.
User Interviews
I interviewed 5 participants across fitness levels and life stages. Each 30-minute session explored their current tracking habits, frustrations, and unmet needs.
P1- Competitive Athlete
Trains 6x/week,cycles bulk/cut phases
"I spend more time logging food than actually eating it. I know what chicken breast has just let me type it fast."
Insight →Power users need a free-text input that parses natural language, not a search-and-select database.
P2- Postpartum Mom
Recovering, breastfeeding, tracking nutrients
"I need to know if I'm getting enough protein and iron, not just calories."."
Insight →Food quality categorization (nutritious/processed/ultra-processed) matters more than just macros for health-focused users.
P3- Tech Professional
"Show me my patterns. Am I actually improving week over week?"
Meal preps, data-driven, wants trends
Insight →Historical trend data and weekly summaries drive long-term engagement more than daily logging alone.
Personas
From the interviews, I distilled two primary personas representing opposite ends of the spectrum ensuring the same interface serves both.
USER FLOWS
Design Principles
Flexible Precision
Same interface serves both, the depth of data entry determines the complexity of output
Progressive Disclosure
Start simple, reveal complexity as users engage
Emotion Aware
No Guilt including patterns, focuses on progress
Education as Needed
Tooltips for beginners, hide able for experts
Consistency> Perfection
Every log adds value, no pressure for complete days
DESIGN SYSTEM
140+ Metrics, 8 Card Types
Green- On Target
Yellow- on attention
Red- Over limit
Gray- No data
Within goal, completed, or inside healthy range
Approaching a limit or at 80–100% of goal
Exceeded cap, missed goal, or concerning level
Nothing logged yet today neutral, no judgment
ONBOARDING STRATEGY
Two paths. Both get to
value immediately.
FEATURES
Key Design Deliverables
CORE EXPERIENCE
AI-Powered Meal Logging
Type "chicken stir-fry with rice" or snap a photo. The AI parses any level of detail, from casual descriptions to gram-precise entries and returns calories, macros, and food quality instantly. No database searching, no barcode scanning.
INSIGHTS
Patterns You'd Miss Alone
Are weekends derailing you? Is protein consistently low at lunch? The design surfaces patterns through nutritious vs. processed food trends, weekday vs. weekend comparisons, and specific actionable suggestions based on actual user data.
HABIT TRACKING
Beyond the Plate
I designed a comprehensive habit tracking system covering hydration, sleep, steps, supplements, and 140+ metrics across 9 categories. One-tap logging with Apple Health auto-sync each metric uses purpose-built card types: gauges, binary indicators, trend lines, and checklists.
DAILY RECAPS
Summaries That Actually Help
End-of-day breakdown: what you ate, how it stacked up against your targets, and one thing to focus on tomorrow. I designed these to be motivational, not judgmental — celebrating consistency over perfection.
WEEKLY PODCASTS
Personalized Audio Recaps
A unique feature I designed: a personalized audio recap of the user's week, patterns, wins, and practical next steps. Listen on your commute or at the gym. This turned data into an engaging narrative experience.
