Adaptive email auto-responder with GPT-4, RAG and human feedback loop

⚙️ Self Learning Agent: AI-Powered Email Auto-Responder that Improves with Feedback

🧑‍💻 Author: LeeWei

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Overview of the n8n Workflow

This n8n workflow builds a self-improving AI agent for handling email responses. It integrates Gmail for incoming messages, uses an AI agent with a Supabase vector store for knowledge retrieval, drafts replies based on dynamic prompts, and evaluates confidence scores. High-confidence drafts are sent automatically, while low-confidence ones are routed to Google Sheets for human review. Feedback from Sheets triggers updates to the prompt or knowledge base, enabling the agent to learn and refine its responses over time. The workflow supports OpenAI and OpenRouter models, with structured output parsing and conditional routing for efficiency.

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How it Works

• Triggers on new Gmail emails, extracts content, and uses an AI agent with company knowledge from Supabase to draft a response. • Assesses confidence; auto-sends high-confidence replies or saves drafts to Google Sheets for human feedback. • Monitors Sheets for updates, extracts feedback via AI, and applies changes—either refining the dynamic prompt or adding new info to the vector store. • Loops back improvements to enhance future responses without manual reconfiguration.