Built a 5-agent restaurant automation system in n8n — here's the full architecture
Hey everyone 👋 Just wrapped up a project I've been building for the past few weeks and wanted to share it here since this community will appreciate the technical side. I built a modular 5-agent AI system for restaurant automation using n8n. Here's the architecture: 🔧 Tech stack: → n8n v2.6 (self-hosted + ngrok) → Supabase (PostgreSQL) — central database → OpenAI GPT-4o-mini + GPT-4o + DALL-E 3 → SerpAPI (Google Maps, TripAdvisor, Yelp scraping) → OpenWeatherMap API → Telegram Bot + Gmail OAuth2 → HTML/JS dashboard on Netlify ⚙️ The 5 agents: 1. Reputation Manager — scrapes reviews from 3 platforms, runs sentiment analysis, upserts to Supabase 2. Reservations Bot — multi-step Telegram conversation flow with session management in Supabase 3. Weather Menu Promoter — fetches weather, matches menu items by weather_tags, sends Telegram recommendations 4. Inventory Manager — reads stock, builds AI prompt, parses JSON response, sends low-stock alerts 5. AI Menu Photographer — dual mode: GPT-4o Vision analysis OR DALL-E 3 generation, stores in Supabase Storage A few things I learned building this: - Merge node must use Append mode (not Choose Branch) to avoid blocking - Telegram Parse Mode should be removed to prevent MarkdownV2 errors - OpenAI response lives at response.output[0].content[0].text Full workflows on GitHub (sanitized, no credentials): github.com/Evgeniy1970-ai/restaurant-ai-suite Happy to answer questions or discuss the architecture. What would you have built differently?