Zefaaf Platform – Real-Time Social Platform with AI Matching
Architected and built the complete frontend for a real-time social platform serving 130,000+ users, featuring AI-powered matching, HD video calls, real-time messaging, and a multi-tenant admin dashboard.
Overview
I architected and engineered the complete frontend ecosystem for Zefaaf, a real-time social platform serving 130,000+ active users. The platform combines AI-powered matching, HD video/voice calling, real-time messaging, and a comprehensive subscription system. Problem: The platform needed to scale to hundreds of thousands of users while maintaining sub-100ms latency for real-time features, supporting multiple languages, and providing a seamless experience across web and mobile. Solution: I built the entire frontend using Next.js with TypeScript, implementing: • Real-time messaging infrastructure using Pusher with <100ms message latency • HD video/voice calling via Agora SDK with auto-reconnect and bandwidth optimization • AI-powered matching flow using Persona SDK, reducing match time by 40% • Multi-tenant RBAC admin dashboard with role-based access control (Admin, Agent, Consultant) • Stripe subscription system with referral flows, increasing conversion by 30% • Scalable i18n architecture supporting 33+ languages with SEO-optimized routing Impact: The platform successfully scaled to 130,000+ concurrent users, achieved 100/100 Lighthouse scores, and maintained real-time messaging latency under 100ms even during peak traffic.
Key Achievements
- Scaled real-time infrastructure to support 130,000+ concurrent users with <100ms message latency
- Engineered AI matching flow reducing match time by 40% through optimized algorithms
- Built multi-tenant RBAC system supporting Admin, Agent, and Consultant roles
- Implemented Stripe subscription flows increasing conversion rates by 30%
- Achieved 100/100 Lighthouse scores through strategic SSR and performance optimization
Impact & Metrics
Active Users
130,000+
Performance
<100ms real-time latency
Improvement
40% faster matching, 30% higher conversion
Problem
In your own words, describe the problem this project solves. Focus on user pain points, business constraints, and why the existing solutions were not good enough.
Solution & architecture
Explain the key technical decisions, how the system is structured (frontend architecture, data flow, state management), and how you balanced DX, performance, and maintainability.
Challenges & learnings
Highlight challenges (performance, edge cases, UX trade-offs) and how you approached them. This is where you can talk about realtime features, i18n, multi-tenant logic, or advanced SEO.