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Project Archive // 2025

Signal 
Intelligence 
Engine 

ServiceFull-Stack SaaS Platform
PartnerBanana Farmer (my own platform)
StatusLive & Scaling
CycleOngoing
Project Overview // Phase 01

Banana Farmer is my own market intelligence platform, not client work. It is a signal-first stock and cryptocurrency ranking system that scores thousands of assets daily and presents momentum signals through a real-time interface. I built it, I operate it, and it runs live today.

Master Architect's Note

"This platform processes more data in a day than most apps see in a month. The architecture had to be ruthlessly efficient: edge-first, cache-heavy, and designed for scale. Every millisecond of latency is a missed signal. I built an intelligence engine that catches momentum before the crowd, and I run it live."

Live System Diagnostic // Node: 0
SignupAuth + BillingMULTI-TENANT COREScaleAsset ID: PROTOCOL-ST-4.0.1 // Signal: 0066FF // NODE: 0
Technical Schematic // Illustrative
01 // THE CHALLENGE

Retail investors consistently chase stocks after they've already moved. By the time news hits mainstream, the opportunity is gone. The challenge was building a system that could ingest massive amounts of market data, score assets using proprietary algorithms, generate AI-powered analysis, and present actionable signals in real-time, all while maintaining sub-second response times.

02 // THE ARCHITECTURE

I engineered a distributed intelligence pipeline with 100+ Cloudflare Workers handling data ingestion, scoring computation, and AI content generation. A proprietary "Ripeness Score" algorithm combines technical momentum, social sentiment, and market structure into a single 0-100 signal. TradingView integration provides professional-grade charting, while Stripe powers the freemium subscription model.

Ripeness Score AlgorithmTypeScript
// Proprietary scoring combines multiple signal sources
interface RipenessFactors {
  technicalMomentum: number;  // RSI, MACD, volume profile
  socialSentiment: number;    // Social mentions velocity
  marketStructure: number;    // Support/resistance levels
  volumeAnomaly: number;      // Unusual volume detection
}

function calculateRipeness(factors: RipenessFactors): number {
  const weights = { tech: 0.4, social: 0.2, structure: 0.25, volume: 0.15 };

  return Math.min(100, Math.round(
    factors.technicalMomentum * weights.tech +
    factors.socialSentiment * weights.social +
    factors.marketStructure * weights.structure +
    factors.volumeAnomaly * weights.volume
  ));
}
Performance Metrics
10,000+Assets Analyzed
100+Background Workers
Real-timeSignal Latency
Execution Detail // The Laboratory
Daily Assets10,000+
throughput pattern
Worker Jobs100+
sync pattern
Update CycleLive
latency pattern
Pro ConversionActive
conversion pattern
Stack Analysis
Next.js 14SupabaseCloudflare WorkersStripeTradingViewDeepSeek AINextAuth.jsPostHog

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