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Multi-agent personal assistant orchestration with GPT-4o & WhatsApp

Amanda BenksAmanda Benks
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2/3/2026
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Description

'Elena AI' is a powerful n8n workflow that transforms your automation platform into a full-fledged, multi-agent AI hub. 🤖✨ By combining Redis state management with specialized “tool” sub-workflows, you can build contextual, scalable, and highly personalized conversational automations for WhatsApp, Telegram, email, and more.

🔥 Key Features

  • Unified Ingestion 📥
    • Webhook trigger for text, audio, image, or document messages
    • Automatic extraction of remoteJid, user ID, and payload metadata
  • Stateful Context 🔄
    • Redis push/get queue to preserve conversation history
    • Seamless handling of follow-ups and multi-turn dialogs
  • Dynamic Routing 🔀
    • Smart Switch logic directs messages to the right agent workflow
    • Agents available:
    • 🗓️ Malu: Google Calendar scheduling & reminders
    • 💰 Maria: Expense logging & budget tracking in Baserow
    • 👥 Mafalda: Contact CRUD operations in Baserow
    • 📸 Marcela: Audio transcription & image analysis
    • ✉️ Martina: Gmail send/receive & template replies
  • Bite-Sized Responses ✂️
    • Splits long AI replies into line-by-line messages
    • Loop node controls rate & order for best UX
  • Flexible Output 📤
    • HTTP Request node to deliver text, media, or files
    • Customize headers, payloads, and endpoints

🎯 Use Cases

  • AI-powered customer support bots
  • Automated lead qualification & follow-up
  • Intelligent scheduling & reminders
  • Expense approval workflows
  • Multimedia content analysis & response

📋 Requirements

  • n8n ≥ 1.0 with Webhook, Redis, SplitInBatches, HTTP Request & Workflow nodes
  • Redis server (connection credentials in n8n)
  • Service accounts / API keys for:
    • Google Calendar (OAuth2)
    • Baserow (API token)
    • Gmail (OAuth2)
    • Messaging API endpoint (HTTP)
  • Environment variables set in n8n:
    • REDIS_HOST, REDIS_PORT, REDIS_PASSWORD
    • GOOGLE_CLIENT_ID, GOOGLE_CLIENT_SECRET
    • BASEROW_API_TOKEN
    • GMAIL_CLIENT_ID, GMAIL_CLIENT_SECRET
    • MSG_API_URL, MSG_API_KEY

🚀 Quick Start

  1. Import the ElenaAI.json into n8n.
  2. Configure credentials and environment variables under Settings → Credentials.
  3. Link sub-workflows (Malu, Maria, Mafalda, Marcela, Martina) by updating their Workflow IDs in the main node.
  4. Test via Execute node or send a sample webhook payload.
  5. Deploy by exposing the Webhook endpoint to your messaging platform.

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n8n Multi-Agent Personal Assistant Orchestration with GPT-4o and WhatsApp

This n8n workflow orchestrates a multi-agent personal assistant, leveraging GPT-4o for intelligent responses and integrating with WhatsApp for communication. It uses a Supabase database for chat memory and allows for dynamic tool calling via other n8n workflows.

What it does

This workflow acts as a central hub for an AI personal assistant, performing the following key steps:

  1. Receives WhatsApp Messages: It listens for incoming messages via a webhook, likely from a WhatsApp integration (though not explicitly defined in the JSON, the directory name hints at it).
  2. Manages Chat History (Redis): It stores and retrieves chat history using a Redis database, ensuring conversational context is maintained.
  3. Determines Agent Action: It uses an "AI Agent" (likely powered by OpenAI's GPT-4o) to analyze the incoming message and decide the appropriate next action.
  4. Conditional Logic for Tool Use: It employs a "Switch" node to route the conversation based on whether the AI Agent decides to use a specific tool (another n8n workflow) or directly respond.
  5. Calls External n8n Workflows as Tools: If a tool is identified, it calls another n8n workflow to perform a specific task (e.g., fetch information, perform an action).
  6. Processes Tool Output: It extracts and formats the output from the called tool workflows.
  7. Generates AI Response: It uses an "OpenAI Chat Model" to generate a natural language response, incorporating any tool output if applicable.
  8. Updates Chat History (Supabase): It stores the AI's response in a Supabase database, maintaining a persistent chat log.
  9. Sends WhatsApp Response: It sends the generated AI response back to the user via WhatsApp (implied by the directory name and the initial webhook trigger).
  10. Handles No-Tool Scenarios: If no tool is needed, it directly generates an AI response and sends it back.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running instance of n8n.
  • WhatsApp Integration: A configured WhatsApp integration that can send messages to and receive messages from the n8n webhook.
  • OpenAI API Key: An API key for OpenAI (specifically for GPT-4o, as hinted by the directory name and the "OpenAI Chat Model" node).
  • Redis Database: Access to a Redis database for storing temporary chat memory.
  • Supabase Database: Access to a Supabase database for persistent chat history.
  • Additional n8n Workflows (for Tools): Other n8n workflows configured as "tools" that the AI Agent can call.

Setup/Usage

  1. Import the Workflow: Import the provided JSON into your n8n instance.
  2. Configure Webhook:
    • Activate the "Webhook" node and copy its URL.
    • Configure your WhatsApp integration to send incoming messages to this n8n webhook URL.
  3. Set up Credentials:
    • OpenAI Chat Model: Configure your OpenAI API key credential.
    • Redis: Set up your Redis database credentials.
    • Supabase: Set up your Supabase database credentials.
  4. Configure AI Agent:
    • The "AI Agent" node will need to be configured with the appropriate model (e.g., gpt-4o) and potentially with descriptions of the "tools" (other n8n workflows) it can call.
  5. Define Tool Workflows: Create separate n8n workflows that serve as "tools." These workflows should accept input and return output in a format the AI Agent can understand. The "Call n8n Workflow Tool" node will be configured to point to these tool workflows.
  6. Activate Workflow: Once all configurations are complete, activate the workflow.

The workflow will then be ready to receive WhatsApp messages, process them with the AI Agent, utilize tools as needed, and respond intelligently.

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