LimaTrome
I developed a full-stack MVP for hiring home services in Lima, connecting clients with professionals for gardening, painting, electrical work, plumbing, cleaning, carpentry, and general maintenance. The project was designed around a problem observed in Lima, Peru: many residential service hires still start through informal recommendations and word of mouth, which makes trust, availability, coverage, and history hard to compare. I chose Peru as an intentional learning scope to study a Latin American market outside my Brazilian context and adapt the product to another city, language, district structure, and service routine.
PROJECT OVERVIEW SUMMARY
Key project indicators
CASE STUDY PROCESS
From context to outcome
CONTEXT — 01
LimaTrome was created as an authorial MVP for the residential services market in Lima, Peru. The starting point was the habit of hiring through personal recommendations: a familiar but hard-to-scale flow when clients need reliable professionals by district, category, and availability.
PROBLEM — 02
Hiring home services depends on trust, location, professional coverage, schedule availability, and clear request information. When the process relies mostly on word of mouth, clients have less visibility into who is available, what area each professional covers, and how previous services were evaluated. The main challenge was turning that informal recommendation flow into structured data, roles, statuses, and matching rules.
MY ROLE — 03
I built the product end to end and used Lima as a deliberate product-discovery exercise outside Brazil. I was responsible for the project definition, interface implementation, API modeling, frontend/backend integration, database flow, tests, fixes, and deploy. I used AI tools as support during development, mainly to research alternatives, review code, validate decisions, and accelerate repetitive tasks, while keeping the architecture, product decisions, integrations, and final implementation under my responsibility.
SOLUTION — 04
The solution combines a Nuxt 3 interface with a Laravel 11 REST API protected by Sanctum. The frontend consumes authenticated API endpoints, Laravel centralizes validation and business rules, and PostgreSQL/Supabase stores users, roles, professionals, districts, requests, schedules, images, notifications, and audit records. Clients can create and track requests, professionals can manage compatible opportunities and weekly availability, and administrators can approve professionals, filter records, paginate lists, audit changes, and manage service orders.
KEY FEATURES — 05
District and category search, client and professional registration, requests with date, time, and photos, customer dashboard, professional dashboard, admin metrics, approval flow, audited edits, weekly agenda, blocks and holidays, status updates, image uploads, rate limiting, legal term acceptance, and feature tests for the main flows.
RESULTS — 06
The MVP turns an informal hiring habit into a structured marketplace base, with separated client, professional, and admin experiences, request management, and a matching algorithm that scores professionals by category, coverage, rating, history, distance, workload, availability, and response time. In a second version, I would improve payment flow, automated WhatsApp communication, richer analytics, and a more complete mobile/PWA experience.
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