SaaS
Fynder.ai
AI-Powered Search & Discovery Platform
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Executive Summary
The Situation:The AI search landscape required a lightning-fast, cross-platform solution capable of parsing massive language models and returning real-time data to users on Web, iOS, and Android.
The Mandate:Architect a scalable multi-platform ecosystem utilizing Next.js for the web interface and Flutter for the native mobile applications, unified by a real-time Firebase and WebSocket backend.
The Result:Successfully launched across all major app stores and web, acquiring over 5,000 active downloads and 10,000+ platform views with highly stable, low-latency AI responses.
Architecture Stack
Flutter
Next.js
TypeScript
BLoC State Management
Firebase
Customer.IO
WebSockets
Stripe
Vercel
AI Integration
Technical Deep-Dive
Overcoming Bottlenecks
Handling continuous AI text generation (streaming responses) across different mobile networks without blocking the UI thread or causing state-management memory leaks in Flutter.
First-Principles Engineering
Implemented strict BLoC (Business Logic Component) state management in Flutter to isolate UI from business logic. Utilized WebSockets for raw streaming data instead of standard REST polling, reducing response latency by over 60%.
Business Impact
Rapid Multi-Platform Launch
Deployed to Web, iOS, and Android simultaneously using a unified codebase philosophy.
Revenue Readiness
Seamlessly integrated Stripe for subscription management across all platforms.
Retention Focused
Customer.IO integration enabled automated engagement pipelines, keeping the 5k+ downloaded user base highly active.