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Client: Half Dozen

Viralytics

AI-powered A&R discovery agent that identifies independent artists with viral momentum across Spotify charts and city playlists

• Cloudflare Workers • Puppeteer Scraping • AI Analysis • Notion Integration

The Challenge

Half Dozen's A&R team needed a way to discover independent artists before they blow up. Manual tracking across multiple chart sources was time-consuming and inconsistent. The solution needed to identify artists with viral momentum and present actionable intelligence.

Technical requirements:

  • — Scrape Spotify charts (Global Daily, City Pulse playlists)
  • — Track chart positions, rank changes, days on chart
  • — Filter for independent artists (non-major label)
  • — Calculate "Viralytics Score" for discovery prioritization
  • — Automatically add qualified artists to Notion for review

System Architecture

Data Flow:

Chart Sources (Spotify, City Pulse)
    ↓
chart-scraper Worker (Puppeteer)
    ↓
chart-service Worker (API + Storage)
    ↓
D1 Database (charts, artists, metrics)
    ↓
viralytics-workflow (Daily 7 AM UTC)
    ↓
AI Analysis (OpenAI + Perplexity)
    ↓
Notion (A&R Review Queue)

Key components:

  • ✓ chart-scraper: Browser Rendering API with Puppeteer for scraping protected charts
  • ✓ chart-service: API orchestrator that fetches, caches, and stores chart data
  • ✓ viralytics-workflow: Daily AI agent that discovers and qualifies artists

AI-Powered Discovery

The viralytics workflow runs 20 SQL queries daily to identify artists with viral potential:

Trending New Entries

New in top 50, last 14 days

Rapid Climbers

8+ position jump in 7 days

Cross-Market Momentum

Charting in 2+ markets

Independent Rising

Non-major label, top 30

Each candidate is scored using the Viralytics Score—a composite metric combining chart velocity, market breadth, and independence status.

Results

4+

Chart sources

Global, Denver, NYC, Austin

Daily

Automated discovery

7 AM UTC workflow

20

Discovery queries

Multi-signal analysis

Production status:

  • ✓ Chart scraping operational (4 sources)
  • ✓ Daily workflow triggering at 7 AM UTC
  • ✓ Notion integration for A&R review queue
  • ⏳ Cloudflare D1 migration in progress (from Neon PostgreSQL)

Applying the Canon

Viralytics applies Tufte's data-ink ratio principle: the system maximizes signal (actionable artist discoveries) and minimizes noise (irrelevant chart data).

The 20-query discovery engine embodies Rams' Principle 10 (as little as possible)—each query targets a specific signal. No query exists without justification.

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