Hey!
I'm sharing an automation system with complete implementation files—no marketing fluff, just working workflows and documentation.
System: Instagram Auto-Responder (n8n-based)
This system handles Instagram DM responses from detection through lead qualification and CRM integration.
What It Actually Does:
Detects new Instagram DMs via Facebook API webhook
Filters senders against do-not-reply lists
Generates personalized responses in under 20 seconds using brand voice
Qualifies leads and recommends products/services
Tags and stores hot leads directly in CRM
Manages follow-up sequences automatically
Technical Implementation:
Webhook processing: Facebook API integration with instant DM detection
Memory management: 40-minute context window using Postgres Chat Memory
RAG system: Supabase vector store with OpenAI embeddings for knowledge retrieval
AI processing: OpenAI Chat Model with custom prompt templates
Document processing: Google Drive integration with text extraction and embedding
Multi-language support: English, Spanish, French, and Portuguese
CRM integration: Automated lead tagging and storage
How It Works:
Webhook receives DM from Facebook API
System checks sender against do-not-reply list
AI agent processes message using RAG and chat memory
Searches vector store for relevant context
Crafts personalized response matching brand voice
Sends reply via Facebook API
Updates CRM with lead information and conversation history
Engineering Note: System requires Instagram app creation in developers.facebook.com. Test the production version by DMing @LaunchpadFast on Instagram.
Real Value: Eliminates support team bloat while maintaining personalization quality. Handles thousands of concurrent conversations with consistent brand voice and sales focus.
What You're Getting:
✅ Complete n8n JSON workflows - Import and run immediately
✅ Prompt templates - Production-tested GPT 4.1-nano prompts (see prompt in AI Agent)
✅ Vector store configuration - Supabase setup with embedding optimization
Access Everything Here: https://drive.google.com/drive/folders/1dlysHmgeGy3OL_HxWWKb5uYhB762dZcC?usp=sharing
For Technical Decision Makers:
These aren't black-box solutions. You get full source code, can modify everything, and own the implementation. Each system is designed to be:
Modular: Swap components as needed
Debuggable: Clear node structure with error handling
Scalable: Same workflow handles varying volumes
Cost-conscious: Optimized API usage patterns
Common Use Cases We've Seen:
SaaS companies automating inbound support and sales
Agencies scaling automation services to their Instagram clients
Support teams increasing output without hiring
Engineering teams freeing up time from repetitive tasks
Want Custom Implementation?
These blueprints are starting points. If you need:
Integration with your existing stack
Custom modifications for your use case
Team training on prompt engineering
Full deployment support
Reply or email [email protected]. We help engineering teams implement and customize these systems, typically seeing first results within days, not months.
Best,
John
P.S. This system is actively used by businesses that rely on Instagram for lead generation and appointment booking. The automation handles the volume while maintaining the personal touch that converts. Ready to eliminate your Instagram response bottleneck?