Automating Venue Research as a Musician

🚀 What I Built

As an independent musician, I spend a lot of time on manual search for venues. Scrolling through websites and looking for contact data takes a lot of time needed for creative work. I built an AI-powered venue discovery tool that analyses musician and venue websites and automatically finds performance opportunities.

✅ The demo video is available here.

✅ The n8n workflow JSON is publicly shared in a GitHub Gist.

✅ All data is tracked in the publicly shared Airtable.

⚙️ What does it do?

The n8n music event aggregator is tool that:

• Scrapes concert pages from musician and venue websites using Bright Data
• Uses n8n AI agent node to extract venue names, locations, dates, and contact information
• Automatically discovers new musicians and venues from the extracted data
• Builds a powerful database of performance opportunities
• Removes duplicates through intelligent AI comparison
• Runs continuously on scheduled triggers to keep the database fresh

*This tool aims to solve the core problem every independent musician faces: finding venues is time-consuming manual work that takes time away from creating music. *

🧱 Architecture

The workflow consists of three parts:

Core venue extraction pipeline

• Trigger: Manual start or run on schedule
• Data Source: Airtable databases for Musicians and Venues with "Pending" status
• Web Scraping: Bright Data extracts raw HTML from concert/event pages
• AI Processing: Claude 3.7 Sonnet analyzes content using structured output parsing
• Database Storage: Venue opportunities saved to "Extracted Events" table

Smart Deduplication System

• AI Comparison: LLM compares new discoveries against existing database
• Duplicate Detection: Handles variations in spelling, formatting, and venue names
• Auto-Creation: New musicians/venues automatically added with "New" status
• Status Tracking: Processed sources marked as "Completed" to prevent reprocessing

Source Discovery Automation

• Google Search Integration: SerpApi finds concert pages for new musicians/venues
• URL Collection: Event page URLs automatically added to database records
• Status Updates: Sources moved from "New" to "Pending" for processing
• Continuous Loop: System continuously discovers and processes new opportunities

📋 AI Model Configuration

• Model: Claude 3.7 Sonnet via OpenRouter
• Temperature: 0.1 for
• Output Format: Structured JSON schema with defined fields
• System Instructions: Optimized for venue/contact information extraction

🎉 Bright Data Verified Node

Bright Data node handles web scraping of event webpages for further AI specific data extraction.

🌟 Inspiration

Like most independent musicians, I spend more time booking gigs than making music. Each venue requires individual research - finding their event calendar, understanding their booking process, identifying the right contact person.

This tool is aimed to solve my personal problem while potentially creating a pipeline that scales to help other independent musicians. Instead of spending weekends researching venues, artists would spend them writing songs. A database would constantly update performance opportunities.