Technical Overview

For CTOs, CIOs, and Technical Decision Makers

Executive Summary

BragBin.Com is a modern, cloud-native photo digitization platform built with industry-standard technologies and best practices. The platform is designed for scalability, security, and maintainability, leveraging serverless architecture, modern frameworks, and proven third-party services.

✓Serverless-first architecture for cost efficiency and scalability
✓Modern tech stack (Next.js, Express.js, MongoDB, AWS S3)
✓AI-powered processing with custom proprietary models
✓Security-first design with JWT authentication and encryption
✓Comprehensive testing with Playwright E2E tests
✓CI/CD automation with Vercel deployment

Technical Architecture

System Overview

Web App (Next.js) → API Server (Express.js) → AI Processing (Custom)
                    ↓                    ↓
              MongoDB Atlas          AWS S3 Storage
                    ↓
              Stripe (Payments)

Architecture Principles

  • •Separation of Concerns: Web app, API, and AI processing are separate services
  • •Serverless-First: Leverage Vercel for automatic scaling and zero server management
  • •Privacy Protection: Customer photos processed using proprietary custom models, never sent to third-party APIs
  • •Data Ownership: Full control over customer data, processing, and retention
  • •Cost Efficiency: Pay-per-use model with serverless infrastructure

Technology Stack

Frontend (Web App)

Framework: Next.js (React) - Server-side rendering, API routes, automatic code splitting

Styling: Tailwind CSS - Utility-first CSS, rapid development

Testing: Playwright - Cross-browser E2E testing

Language: TypeScript - Type safety, better IDE support

Deployment: Vercel - Automatic CI/CD, edge network, zero-config

Backend (API)

Framework: Express.js (Node.js) - Mature ecosystem, RESTful API design

Database: MongoDB (MongoDB Atlas) - Flexible schema, horizontal scaling

Storage: AWS S3 - Industry standard, scalable, encryption at rest

Authentication: JWT - Stateless, scalable, industry standard

Payments: Stripe - PCI-compliant, webhook support

Email: Resend - Modern API, deliverability

Security: Rate limiting - Abuse prevention, DDoS protection

AI Processing (Custom Proprietary Models)

Language: Python

Models: Custom proprietary models for photo enhancement and restoration

Processing: Dedicated processing infrastructure

Storage: AWS S3 for input/output

Queue: MongoDB job queue (status: pending → processing → completed)

Development Team & Credits

Created By

Development Organization: e:\findajob

  • • Location: Development workspace at e:\findajob
  • • Approach: Modern development practices, AI-assisted development
  • • Methodology: Linear-driven workflow, gate-based delivery

Development Approach

AI-Assisted Development:

  • • Cursor AI: Primary development environment
  • • Linear MCP: Issue tracking and project management
  • • MCP DevTools: Browser automation and testing
  • • Agent Rules: Comprehensive development guidelines

Quality Standards:

  • • Excellence Framework: Gate-based delivery, test-before-complete
  • • Gate-Based Delivery: 30/60/90-day milestones
  • • Test-Before-Complete: E2E testing before deployment
  • • Documentation-First: Architecture docs before implementation

Security & Compliance

Authentication & Authorization

  • • JWT-based authentication: Stateless, scalable
  • • Password hashing: bcryptjs (10 rounds)
  • • Email verification: Required for account activation
  • • Magic links: Passwordless login option
  • • Password reset: Secure token-based flow

Data Protection

  • • Encryption at rest: AWS S3 (SSE-S3)
  • • Encryption in transit: HTTPS/TLS for all connections
  • • Private storage: S3 buckets with block public access
  • • IAM credentials: Least privilege access
  • • Secrets management: Environment variables (never in code)

Privacy & Compliance

  • • Data ownership: Customer data never shared with third parties
  • • Local AI processing: Photos processed using proprietary custom models
  • • Consent management: Explicit consent for scan & destroy
  • • Terms & Privacy: Comprehensive legal documentation
  • • Audit trail: MongoDB logging for compliance

Scalability & Performance

Current Capacity

  • • Web App: Vercel serverless (unlimited scaling)
  • • API: Vercel serverless functions (automatic scaling)
  • • Database: MongoDB Atlas (M10 cluster, scalable)
  • • Storage: AWS S3 (unlimited capacity)
  • • AI Processing: Manual workstation (100-500 photos/day)

Performance Optimizations

  • • Next.js: Automatic code splitting, image optimization
  • • Serverless: Zero cold starts with Vercel
  • • Edge Network: Global CDN for static assets
  • • Database Indexing: MongoDB indexes on frequently queried fields
  • • S3 Presigned URLs: Direct client-to-S3 downloads

API Architecture

RESTful Design

RESTful API architecture with standard HTTP methods and JSON responses

API Capabilities

RESTful API supporting:

  • • User authentication and authorization
  • • Photo upload and job management
  • • Subscription and payment processing
  • • Mail-in order management
  • • Affiliate tracking and analytics

Technical Documentation

Product Roadmap

Strategic product roadmap with planned features, phases, and priorities

Development Timeline

Gate-based development timeline with milestones and review points

Release Notes

Version history, release notes, and changelog

Technical Contact

For technical questions or partnership inquiries

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