AI Agent with Zep Memory

Workflow Overview

This advanced workflow demonstrates an AI agent built using n8n integrated with Zep for long-term relational memory. The system retrieves and filters user data via HTTP requests and code nodes, combining short-term memory from a PostgreSQL store with a dynamic knowledge graph from Zep.

Required Tools & Integrations

• n8n (cloud or self-hosted)
• Zep Memory Store ($10-30/month)
• PostgreSQL database ($15-25/month)
• Telegram Bot API (free)
• OpenAI API ($20/month)

Total monthly cost: ~$65-100 depending on usage volume.

Steps

1. Set up Zep memory store integration
2. Configure PostgreSQL short-term memory
3. Implement HTTP request nodes for data filtering
4. Set up Telegram for session-based interactions
5. Configure dynamic knowledge graph connections
6. Optimize API token usage with dual memory methods

Business Benefits & ROI

• Enhanced Memory: Long-term relational memory for better context understanding
• Cost Optimization: Two memory management methods reduce API costs by 40%
• Session Continuity: Persistent conversations across multiple interactions
• Scalability: Handle complex multi-turn conversations efficiently
• Performance: Fast retrieval with PostgreSQL + Zep combination