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Legacy System Modernization

San Pedro MotoCare

From paper notebooks and WhatsApp chaos to a cloud-native, AI-augmented motorcycle service platform — zero downtime migration.

📍 San Pedro Garza García, NL, México·🏍️ Motorcycle Service & Repair·⏱️ 8-week delivery
100%
Processes Digitized
60%
Fewer No-Shows
Faster Billing
<5s
Customer History Access

The Problem

San Pedro MotoCare is a well-established motorcycle repair shop with a loyal client base built over a decade. Despite strong technical expertise, the business was hemorrhaging revenue and customer satisfaction through operational inefficiency rooted in manual, disconnected workflows.

The owner managed everything from memory and paper: customer names, motorcycle specs, service histories, parts levels, pricing. When he wasn't in the shop, nothing could move. A single technician calling in sick could create a cascade of missed appointments, angry customers, and lost revenue — because nothing was documented in an accessible system.

The most damaging invisible cost: zero customer retention system. Loyal clients who serviced annually weren't being reminded. No-shows happened weekly. Parts stock-outs were discovered only when a customer was already waiting.

Before & After

Customer Records
Before

Paper notebooks, inconsistent handwriting, impossible to search. Customer history lost when notebooks fill up.

After

Firestore CRM: full motorcycle history, photos, service notes, contact data — searchable in under 2 seconds.

Appointment Scheduling
Before

WhatsApp messages, verbal agreements, double-bookings, forgotten appointments, no reminders.

After

Google Calendar integration with automated WhatsApp Business reminders 24h and 1h before service.

Parts Inventory
Before

Excel spreadsheet updated manually once a week. Frequent stock-outs discovered only when a customer needed a part.

After

Real-time Firestore inventory with low-stock alerts via email/WhatsApp. Purchase orders auto-drafted when minimum threshold hit.

Billing & Receipts
Before

Carbon-copy paper invoices. No totals tracking, no tax record, lost copies.

After

PDF receipts generated in 1 click with QR code for digital verification. Monthly revenue reports auto-exported to BigQuery.

Customer Follow-Up
Before

Zero systematic follow-up. Customers forgot annual maintenance dates. Revenue lost to competitors.

After

Automated follow-up sequences: post-service satisfaction, 6-month checkup reminder, annual maintenance alert.

Business Analytics
Before

No data. Owner had zero visibility into which services generated most revenue, peak hours, or customer retention rates.

After

BigQuery dashboard: revenue by service type, technician performance, peak hours, customer LTV, repeat rate tracking.

Migration Roadmap

01

Discovery & Audit

1 week
  • On-site process mapping — every manual touchpoint documented
  • Pain point severity scoring with the owner and 2 technicians
  • Data recovery: 3 years of paper records digitized and structured
  • Tech debt assessment: existing WhatsApp history parsed for customer patterns
02

Core Platform Build

3 weeks
  • Firestore schema design for customers, motorcycles, services, parts, invoices
  • Next.js admin dashboard: customer lookup, service intake form, technician assignment
  • Mobile-first design: technicians use tablets in the workshop, not desktops
  • PDF invoice generator with QR-code verification and company branding
03

Automation Layer

2 weeks
  • WhatsApp Business API integration: appointment confirmations & service-ready alerts
  • Google Calendar sync: technician schedules, customer appointments, parts deliveries
  • Cloud Run scheduled jobs: daily inventory check, weekly revenue digest email
  • Automated follow-up sequences: 3-day post-service satisfaction, 6-month checkup nudge
04

Analytics & AI Layer

1 week
  • BigQuery pipeline: Firestore → BigQuery nightly export via Dataflow
  • Revenue dashboard: by service type, technician, day of week, motorcycle brand
  • AI Diagnosis Assistant: customer describes symptoms → Gemini suggests likely service
  • Predictive inventory: BigQuery ML flags parts likely to stock-out based on seasonality
05

Training & Go-Live

1 week
  • 2-hour training session with all staff — zero technical knowledge required
  • Parallel run: 2 weeks operating both old and new systems simultaneously
  • Hard cutover: paper system retired, full digital operation from day one
  • 30-day hypercare support with direct WhatsApp line to TOFAI engineering

Tech Stack

Next.js 14
Admin dashboard & customer-facing portal
Firebase Firestore
Real-time CRM, inventory & appointment data
Cloud Run
Serverless API for automation workflows
BigQuery
Business analytics & revenue reporting
WhatsApp Business API
Automated reminders & customer notifications
Google Calendar API
Appointment scheduling & technician calendar
Tailwind CSS
Mobile-first responsive UI
AI Diagnosis Assistant
Gemini-powered symptom-to-service suggestion

The Invisible ROI: Data as a Business Asset

The most transformative outcome wasn't the efficiency gains — it was the data. Before migration, the owner had no answer to "which service is most profitable?" or "when is my busiest week?" After 90 days on the platform, BigQuery revealed:

  • Full engine tune-ups were 4× more profitable per hour than tire changes — but were underpriced.
  • 62% of no-shows happened on Fridays. A Friday appointment pricing adjustment reduced it to 18%.
  • Honda CB500 owners had a 91% return rate. Yamaha MT owners had 34%. Different follow-up strategies deployed for each.