Product Requirements Document: FleetFlow Maintenance Pro

1. Executive Summary

FleetFlow Maintenance Pro is a high-performance, mobile-first operations platform designed to eliminate commercial fleet downtime caused by manual tracking errors and missed service intervals. By leveraging AI-powered VIN scanning, "Local-First" data synchronization, and automated maintenance scheduling, the app provides fleet managers and drivers with a real-time, high-integrity health dashboard for their entire vehicle registry.

2. Problem Statement

Fleet managers currently rely on fragmented manual logs, spreadsheets, or outdated software that lacks mobile accessibility. This leads to:

Costly Downtime: Missed preventive maintenance resulting in catastrophic engine/part failure.
Data Inaccuracy: Manual VIN and odometer entry errors (typos) leading to incorrect parts ordering and non-compliance.
Visibility Gaps: Drivers in remote areas with poor connectivity cannot log data, leaving managers "blind" to vehicle health for days.

3. Goals & Success Metrics

Goal 1: Reduce unscheduled maintenance downtime by 20% within the first six months.
Goal 2: Achieve 99.9% VIN data accuracy through automated OCR and NHTSA validation.
Goal 3: Ensure 100% data availability in offline/low-connectivity environments.
Success Metric: Average time to log a service event should be under 45 seconds.

4. User Personas

5. User Stories

As a Driver, I want to scan a barcode or text VIN so that I don't have to manually type 17 characters.
As a Driver, I want to log my odometer reading even when I have no cell service so that my records stay up to date.
As a Manager, I want to see a Red/Yellow/Green status for every vehicle so that I can prioritize repairs.
As a Technician, I want to upload a photo of a receipt or work order so that there is a digital paper trail for every service.
As a Manager, I want to receive a push notification when a vehicle is within 500 miles of a required oil change.

6. Functional Requirements

6.1 Vehicle Onboarding & VIN Scanning

The system shall use Anyline SDK or Vision Camera v5.x to scan VINs from windshields and door jambs.
The system shall validate the 17-digit VIN using the NHTSA v4.01 API to auto-populate Make, Model, and Year.
Manual override shall be available for legacy vehicles (pre-1981).

6.2 Odometer & Usage Tracking

Daily odometer entry with automated mileage calculation since the last entry.
Validation logic to prevent "mileage rollback" entries (e.g., current entry cannot be lower than the previous entry).

6.3 Maintenance Scheduling & Reminders

Recurring triggers based on mileage (e.g., every 5,000 miles) or time (e.g., every 6 months).
Automated push notifications and email alerts via SendGrid.

6.4 Service Logs & History

Digital repository for all service events including cost, technician name, and part numbers.
Camera integration for receipt and work order photo uploads.

7. Technical Requirements

7.1 Tech Stack (2026 Standards)

Frontend: React Native 0.83.x (Expo SDK 55) with New Architecture (Fabric/TurboModules) enabled.
State Management: TanStack Query v5 (Server) + Zustand (Local).
Local Storage: WatermelonDB for relational local-first data; MMKV for high-speed caching.
Backend: Node.js 22 (LTS) with Express.
Database: PostgreSQL 17 with BRIN indexing for high-frequency logs and UUID v7 for primary keys.
Authentication: Auth0 with Role-Based Access Control (RBAC) and CIBA for high-risk technician actions.

7.2 Integrations

NHTSA vPIC API (v4.01): For VIN decoding.
Google Cloud Vision API: For OCR processing of physical receipts.
Anyline SDK: Specialized automotive OCR for metallic/curved surfaces.

8. Data Model

8.1 Vehicle Entity

id: UUID v7 (Primary Key)
vin: String (Unique, 17 chars)
make_model_year: String (From NHTSA)
current_odometer: Integer
status: Enum (HEALTHY, WARNING, CRITICAL)
organization_id: UUID (Multi-tenant support)

8.2 ServiceRecord Entity

id: UUID v7
vehicle_id: FK -> Vehicle.id
service_type: String (e.g., "Brake Pad Replacement")
odometer_at_service: Integer
receipt_url: String (S3 Link)
completed_at: Timestamp

9. API Specification

`POST /api/v1/vehicles/decode`

Request: { "vin": "1234..." }
Response: { "make": "Freightliner", "model": "Cascadia", "year": 2024, "status": "valid" }

`PATCH /api/v1/vehicles/:id/odometer`

Request: { "reading": 55000, "timestamp": "2026-01-15T10:00:00Z" }
Response: 200 OK (Triggers maintenance check in background)

10. UI/UX Requirements

Dashboard: A "Traffic Light" system (Red/Yellow/Green) for fleet health.
Scan Interface: A camera overlay with a "Region of Interest" (ROI) box specifically sized for VIN plates.
Offline Indicator: A subtle sync status icon (Cloud-check or Cloud-sync) showing pending uploads.
Accessibility: High-contrast buttons and large input fields for drivers wearing work gloves.

11. Non-Functional Requirements

Performance: UI must maintain 60fps; JS execution off-loaded via React Native Worklets.
Offline Mode: App must allow full logging functionality without a network connection.
Security: AES-256 encryption at rest; JWT-based API authentication.
Scalability: Database partitioning via pg_partman to handle millions of odometer logs.

12. Out of Scope

Real-time GPS turn-by-turn navigation.
Payroll or driver salary management.
Direct parts purchasing/e-commerce integration (Phase 2).

13. Risks & Mitigations

14. Implementation Tasks

Phase 1: Project Setup & Infrastructure

[ ] Initialize project with React Native 0.83 and Expo SDK 55
[ ] Enable New Architecture (newArchEnabled=true in gradle.properties)
[ ] Set up Node.js 22 Express server with TypeScript
[ ] Configure PostgreSQL 17 with UUID v7 extension
[ ] Initialize Auth0 tenant and define RBAC roles (Driver, Manager, Technician)

Phase 2: Core Data & Offline Engine

[ ] Set up WatermelonDB schema for Vehicles and Odometer Logs
[ ] Implement MMKV for local preference caching
[ ] Build background sync worker using react-native-background-actions
[ ] Implement exponential backoff for failed sync attempts

Phase 3: VIN & Odometer Features

[ ] Integrate Anyline SDK for VIN scanning
[ ] Create Node.js service for NHTSA v4.01 API integration
[ ] Build Odometer entry UI with "mileage rollback" validation
[ ] Implement BRIN indexing on Odometer table for performance

Phase 4: Fleet Management Dashboard

[ ] Build "Traffic Light" Fleet Health Dashboard
[ ] Implement TanStack Query for real-time dashboard updates
[ ] Create PDF report generator for DOT compliance
[ ] Configure SendGrid for automated service reminders

Phase 5: Security & Quality Assurance

[ ] Implement AES-256 encryption for local storage
[ ] Perform load testing on PostgreSQL partitioning
[ ] Conduct field testing in low-connectivity zones
[ ] Finalize CI/CD pipeline with automated Play Store/App Store deployments