🧠 RAG-Based Customer Support Agent (GPT-5 + Telegram) Description: This workflow builds a powerful Retrieval-Augmented Generation (RAG) Customer Support Agent that interacts with users directly through Telegram using the GPT-5 model. It combines real-time conversational capabilities with context-aware responses by leveraging vector search via Pinecone, making it ideal for automated, intelligent support systems. Watch Video Tutorial Build on Workflows Like These: https://www.youtube.com/@Automatewithmarc 💬 Key Features: Telegram Integration: Listens to customer queries via the Telegram Trigger node and sends back intelligent responses in the same chat. GPT-5 Agent (LangChain): A powerful AI agent node orchestrates the conversation using OpenAI's GPT-5 model. Contextual Memory: A Memory Buffer stores the last 15 interactions per user to provide more personalized and coherent multi-turn conversations. RAG with Pinecone: Integrates with Pinecone to fetch relevant answers from your “Customer FAQ” vector namespace, enabling grounded and accurate responses. Embeddings Generation: Uses OpenAI’s Embeddings node to process and vectorize documents for retrieval.
Tags
Embeddings OpenAI
OpenAI Chat Model
Pinecone Vector StoreSSimple Memory
TelegramRelated workflows
See all AI Automation→Handle WhatsApp sales inquiries with OpenAI, Pinecone, Google Calendar, and Slack
Quick overview This workflow handles inbound WhatsApp Business messages with an OpenAI-powered sales agent that uses Pinecone RAG for product answers and Google Calendar tools for scheduling, then either replies on WhatsApp or hands the conversation to Slack, with Slack-based error alerts. How it works Triggers on every inbound WhatsApp Business message and checks whether the payload contains a text body. Drops non-text messages (such as images or voice notes) and continues only with text conversations. Uses an OpenAI chat model with per-customer session memory to generate a concise sales reply and decide whether a human handoff is needed. Lets the agent query a Pinecone-backed product catalog via OpenAI embeddings to answer pricing, specs, and availability questions. Lets the agent check availability and book appointments in Google Calendar when the customer requests scheduling. Parses the agent’s HANDOFF flag and either posts the customer message plus draft reply to a Slack channel or sends the reply back to the customer on WhatsApp. Sends a Slack alert to an ops channel if any step in the workflow fails. Setup Connect WhatsApp Business Cloud credentials and set the WhatsApp Phon
SAI chatbot that can search the web
This workflow is designed for dynamic and intelligent conversational capabilities. It incorporates OpenAI's GPT-4o model for natural language understanding and generation. Additional tools include SerpAPI and Wikipedia for enriched, data-driven responses. The workflow is triggered manually, and utilizes a 'Window Buffer Memory' to maintain the context of the last 20 interactions for better conversational continuity. All these components are orchestrated through n8n nodes, ensuring seamless interconnectivity. To use this template, you need to be on n8n version 1.50.0 or later.
SAI agent chat
This workflow employs OpenAI's language models and SerpAPI to create a responsive, intelligent conversational agent. It comes equipped with manual chat triggers and memory buffer capabilities to ensure seamless interactions. To use this template, you need to be on n8n version 1.50.0 or later.