Products and systems built around real user needs

Selected work across native mobile, frontend systems, and focused hackathon products—showing the problem, my contribution, the implementation, and the evidence available.

Current flagship: CloseCut 1.0 is a native iOS product I designed, engineered, validated, and publicly shipped. View the case study below.

2nd Place · HDC Brasil 2025 Award-winning AI Product

HoneyRoute

Offline-first apiary intelligence PWA for hive health monitoring and beekeeper decision support.

HoneyRoute onboarding welcome screen
Onboarding and first-run setup
HoneyRoute login authentication screen
Secure login experience
HoneyRoute home dashboard
Hive health dashboard
HoneyRoute new hive creation form
Create and manage new hives
HoneyRoute new apiary setup and configuration
Apiary setup and configuration
HoneyRoute apiary details and hive health status
Detailed hive health status
HoneyRoute apiary health history timeline and trends
Health history and trend analysis
HoneyRoute AI health recommendations and insights
AI recommendations and insights
HoneyRoute evidence photos and diagnostic data
Diagnostic evidence and reports
HoneyRoute AI analysis results and predictions
AI-driven predictions
HoneyRoute historical data and long-term trends
Historical trends and long-term analysis
HoneyRoute alerts and notifications management
Alerts and notification controls
HoneyRoute map view of apiary locations
Location mapping for apiaries
HoneyRoute user settings and app preferences
User account settings

HoneyRoute is an AI-assisted, offline-first PWA designed for beekeepers working in low-connectivity rural environments. Built in 48 hours at HDC Brasil, it combines hive records, health observations, diagnostic evidence, and recommendation flows into a practical field tool.

Offline-first PWA designed for rural beekeeping workflows
AI-assisted diagnostics for hive health observations and recommendations
48-hour build from concept to working competition prototype
ReactNode.jsPWAAI/MLHuawei Cloud
2nd Place · HDC México 2024 Award-winning AI Product

EcoVentus

UAV mission planning and monitoring platform for environmental intelligence.

EcoVentus main dashboard showing UAV mission planning interface with map and controls

Mission Planning Dashboard

EcoVentus real-time monitoring view displaying drone telemetry and flight data

Real-time Telemetry

EcoVentus environmental monitoring dashboard with sensor data visualization

Environmental Sensors

EcoVentus mission analytics showing route optimization and performance metrics

Route Optimization

EcoVentus UAV status panel with battery levels and system diagnostics

System Diagnostics

EcoVentus weather integration showing environmental conditions for flight planning

Weather Integration

EcoVentus mission history and completed flight logs

Mission History

EcoVentus detailed reports and analytics for mission outcomes

Analytics Reports

EcoVentus incident detection and emergency response interface

Incident Management

EcoVentus 3D virtual navigation and terrain visualization

3D Navigation

EcoVentus project information and system specifications

System Overview

EcoVentus is an AI-driven web platform for UAV mission planning, live monitoring, and analytics. Built in 48 hours at HDC México, the system explored how drone operations could support precision agriculture, environmental monitoring, and mission-level decision support.

Mission planning with map-based route visualization
48-hour build from concept to working dashboard
Real-time monitoring interface for UAV operations
Next.jsReactPythonFlaskMongoDBLeafletHuawei Cloud
AI Product Frontend System Product Design

The Signature Experience

Luxury fragrance discovery system for identity-first recommendations and comparison flows.

The Signature Experience landing page and fragrance discovery hero
Landing and luxury discovery entry
The Signature Experience onboarding questionnaire for scent identity
Identity-first onboarding flow
The Signature Experience profile decoding and recommendation transition
Profile interpretation
The Signature Experience scent mirror with visual aura scales
Interactive Scent Mirror
The Signature Experience skin and scent fit questionnaire
Skin and scent refinement
The Signature Experience signature ritual fragrance selection screen
Signature Ritual selection
The Signature Experience confidence scores and fragrance comparison
Confidence scoring
The Signature Experience final signature fragrance confirmation
Signature confirmation
The Signature Experience aura card shareable profile screen
Aura Card profile
The Signature Experience fragrance wardrobe and growth system
Fragrance wardrobe
The Signature Experience refill and loyalty journey screen
Refill and loyalty journey

An immersive fragrance discovery experience designed around identity, comparison, and confidence. The product turns preference discovery into a guided frontend journey with interactive profiling, confidence scoring, scent comparison, wardrobe logic, and post-selection feedback loops.

10-stage journey from onboarding to loyalty flow
Recommendation logic with profile-based confidence scoring
Retention-ready UX with email capture, local persistence, and feedback loops
ReactTypeScriptViteFramer MotionReact RouterVercel AnalyticsUX Strategy
Top 12 · HackNation Award-winning AI Product

CongestionAI

Traffic-aware departure planning for smarter mobility decisions.

CongestionAI home tab with trip planning and departure window setup
Trip planning setup
CongestionAI result tab with best departure recommendation and ETA
Best departure recommendation
CongestionAI result tab showing route alternatives and congestion insights
Route alternatives
CongestionAI forecast tab with future departure recommendations
72-hour forecast
CongestionAI history tab with saved trips and performance trends
Saved trip history
CongestionAI settings tab with planner defaults and savings preferences
Planner settings
CongestionAI forecast and heatmap visualization
Forecast heatmap
CongestionAI settings and trip personalization panel
Personalization panel

CongestionAI is a mobility planning web app that helps drivers decide when to leave, not just which route to take. It compares departure windows, estimates traffic-aware ETA, scores congestion risk, and highlights savings in time, fuel, money, and CO2.

72-hour forecast for flexible trip planning
ETA sampling powered by Google Routes API
Top 12 HackNation competition placement
Next.jsReactTypeScriptGoogle Routes APIGoogle Places APIRisk Scoring
AI Product Frontend System

BlueShelf AI

AI-assisted pantry management with product detection, inventory tracking, and recipe suggestions.

BlueShelf AI inventory dashboard
Inventory dashboard
BlueShelf AI item inventory view
Item status view
BlueShelf AI product detection screen
AI-assisted product detection
BlueShelf AI recipe suggestion screen
Recipe suggestions
BlueShelf AI pantry recommendations
Pantry recommendations
BlueShelf AI personalized pantry recommendations
Personalized recommendations
BlueShelf AI inventory insight screen
Inventory insights
BlueShelf AI product management screen
Product management
BlueShelf AI recipe and pantry planning screen
Pantry planning

BlueShelf AI is a polished household inventory app built with Next.js, Material UI, Supabase, and OpenAI. It supports CRUD product management, image uploads, AI-assisted photo analysis, inventory insights, and recipe suggestions based on items already in stock.

Full CRUD product and stock management
AI-assisted analysis for product photos and recipe generation
Modern stack with Next.js, Supabase Storage, and OpenAI APIs
Next.jsReactMaterial UISupabaseOpenAI API
Professional Work Mobile

Android Commerce Platform

Client marketplace app built at Xolotl Creative Labs with authentication, catalog, cart, and order flows.

Android commerce app catalog screen
Catalog browsing
Android commerce app product details screen
Product details
Android commerce app cart and checkout flow
Cart and checkout flow
Android commerce app order management screen
Order management
Android commerce app order status screen
Order status flow

A professional Android marketplace build developed at Xolotl Creative Labs. I contributed to core customer-facing flows including authentication, product catalog browsing, cart management, order processing, and REST API integration within a Scrum-based delivery process.

Authentication flow for customer access and session handling
Commerce flows across catalog, cart, and order management
Team delivery with REST API collaboration and Scrum ceremonies
KotlinJavaAndroid StudioREST APIsScrum

CloseCut — From personal project to shipped iOS product

CloseCut is a private, local-first movie and series Journal built on one idea: what stayed with you matters more than a score. I took it from product definition and UX through native implementation, beta validation, production debugging, and App Store release.

CloseCut app icon

CloseCut

SwiftUI · SwiftData · Firebase · Product Design

The product keeps personal memories private by default, supports fast past-watch capture with Quick Add, uses Journal context to make QuickPick decisions easier, and brings in lightweight Circle context only when someone explicitly chooses to share.

Product and experience

“More than ratings” became a private-by-default memory system spanning Journal entries, Quick Add, Want to Watch, QuickPick, and intentionally lightweight Circles.

Architecture and craft

I built the native experience with SwiftUI, SwiftData, local-first persistence, and supported Firebase synchronization, while covering privacy, accessibility, localization, testable domain logic, and release engineering.

Production debugging

Shortly before release, a TestFlight-only watchdog crash appeared in the full Journal flow. I traced it through iOS crash logs to SwiftUI layout and focus invalidation, stabilized the flow, and validated the fix on physical devices before submitting a new build.

Foundation

Product definition

Defined a private, mood-aware way to remember what someone watched, when they watched it, and why it mattered—without turning the product into a public ratings feed.

Design

UX and product system

Designed onboarding, Quick Add, detailed memories, personal history, QuickPick, settings, and explicit Circle sharing across accessible, localized flows.

Engineering

Native iOS implementation

Built the app with SwiftUI, SwiftData, Firebase authentication, supported synchronization, local-first persistence, validation, and testable domain logic.

Validation

TestFlight and release hardening

Used beta feedback, real-device testing, crash logs, and production debugging to harden full Journal flows before release.

Live

CloseCut 1.0 shipped

CloseCut 1.0 is publicly available on the App Store. The product is now entering real-user feedback and continued iteration without moving away from its private, memory-first foundation.