Create a two-way WhatsApp + Telegram integration for 10k+ customer support chats

Name: Create a two-way WhatsApp + Telegram integration for 10k+ customer support chats
Availability: InStock
Rating: 4.5 (93 reviews)
Author: Ruthwik

$20/month : Unlimited workflows

2500 executions/month

Try free

THE #1 IN WEB SCRAPING

Scrape any website without limits

Try free

HOSTINGER 🎉 Early Black Friday Deal
DISCOUNT 20%

Self-hosted n8n

Unlimited workflows - from $4.99/mo

Try free

#1 hub for scraping, AI & automation

6000+ actors - $5 credits/mo

Try free

⚡ Next-Gen Customer Support: Two-Way WhatsApp + Telegram Integration for 10k+ Clients

Who is this workflow for

This workflow is designed for customer support teams, e-commerce founders, and operations managers who want to handle thousands of customer queries seamlessly. Instead of building a brand-new chat application, it leverages WhatsApp (where customers already are) and Telegram (where your support team operates) to create a scalable, topic-based support system.

If you are a brand handling 1000s of daily WhatsApp customer messages and need a structured way to map each customer into a dedicated support thread without chaos, this workflow is for you.

What it does / How it works

This two-way n8n automation bridges WhatsApp and Telegram by creating one Telegram forum topic per customer and syncing messages both ways:

Incoming WhatsApp → Telegram
- When a new WhatsApp message arrives, the workflow checks if the customer already has a topic in Telegram.
- If yes → The message is forwarded into that existing topic.
- If no → A new topic is created automatically, the mapping is saved in the database, and the message is posted there.
- Result: every customer has a dedicated thread in your Telegram supergroup.
Outgoing Telegram → WhatsApp
- When a support agent replies in a Telegram topic, the workflow looks up the linked WhatsApp number.
- The reply is sent back to the customer on WhatsApp, preserving context.
- Result: two-way synced conversations without building a custom app.

How to set it up

Configure WhatsApp Cloud API
- Create a Meta Developer account and register a WhatsApp Business number.
- Generate an access token and phone number ID.
Configure Telegram Bot
- Use BotFather to create a bot and enable it in a Telegram Supergroup with Topics.
- Get the chat_id and allow the bot to create/send messages in topics.
Database (Supabase/Postgres)
- Create a table wa_tg_threads to map phone_e164 ↔ telegram_topic_id ↔ supergroup_id.
n8n Workflows
- Workflow A: WhatsApp → Telegram
  - Trigger: WhatsApp Webhook
  - Steps: Lookup customer → If exists send to topic, else create topic → Save mapping → Forward message.
- Workflow B: Telegram → WhatsApp
  - Trigger: Telegram Webhook
  - Steps: Filter only topic replies → Lookup mapping → Send WhatsApp message.
Testing
- Send a WhatsApp message → Check Telegram topic created.
- Reply in Telegram topic → Ensure customer receives WhatsApp reply.

Requirements

A free or paid n8n instance (self-hosted or cloud).
WhatsApp Cloud API credentials (phone number ID + access token).
Telegram Bot token with access to a Supergroup with Topics enabled.
A Postgres/Supabase database to store thread mappings.
Basic familiarity with editing HTTP Request nodes in n8n.

How to customize the workflow

Brand personalization: Pre-populate first message templates (thank you, order status, delivery updates).
Routing rules: Assign specific agents to certain topics by ID ranges.
Integrations: Extend to CRMs (HubSpot, Zoho) or support platforms (Freshdesk, Zendesk).
Notifications: Push high-priority WhatsApp queries into Slack/Teams for instant alerts.
Archival: Auto-close inactive topics after N days and mark customers as dormant.

Why Telegram instead of building a new App

The client's requirement was clear: use an existing, reliable, and scalable chat platform instead of building a new app from scratch.

Telegram Supergroups with Topics scale to 100,000+ members and millions of messages, making them ideal for managing 10k+ customer threads.
Agents don't need to install or learn a new tool---they continue inside Telegram, which is fast, free, and mobile-friendly.
Building a custom chat app would require authentication, push notifications, scaling infra, and UX---all solved instantly by Telegram.

This decision saves development cost, accelerates deployment, and provides proven scalability.

Why this improves support productivity

Organized by customer: Each WhatsApp number has its own Telegram topic.
No missed messages: Agents can quickly scroll topics without drowning in one endless chat.
Two-way sync: Replies flow back to WhatsApp seamlessly.
Scales automatically: Handle 10k+ conversations without losing track.
Leverages existing tools: WhatsApp (customers) + Telegram (agents).

Result: faster responses, better tracking, and zero need to reinvent chat software.

Ruthwik

0 workflows

Nodes

set gmail telegram agent google-gemini

Complexity

advanced

Published 07 Sept 2025

Likes 0

View on n8n.io Download Workflow

✨

Share Your Workflow

Have a great workflow to share? Join the n8n Creator Hub and help the community!

Submit Your Template How to Submit

Related Workflows

Build a website-powered customer support chatbot with Decodo, Pinecone and Gemini

**Categories:** Business Automation, Customer Support, AI, Knowledge Management This comprehensive workflow enables businesses to build and deploy a custom-trained AI Chatbot in minutes. By combining a sophisticated data scraping engine with a RAG-based (Retrieval-Augmented Generation) chat interface, it allows you to transform website content into a high-performance support agent. Powered by **Google Gemini** and **Pinecone**, this system ensures your chatbot provides accurate, real-time answers based exclusively on your business data. ### **Benefits** * **Instant Knowledge Sync** - Automatically crawls sitemaps and URLs to keep your AI up-to-date with your latest website content. * **Embeddable Anywhere** - Features a ready-to-use chat trigger that can be integrated into the bottom-right of any website via a simple script. * **High-Fidelity Retrieval** - Uses vector embeddings to ensure the AI "searches" your documentation before answering, reducing hallucinations. * **Smart Conversational Memory** - Equipped with a 10-message window buffer, allowing the bot to handle complex follow-up questions naturally. * **Cost-Efficient Scaling** - Leverages Gemini’s efficient API and Pinecone’s high-speed indexing to manage thousands of customer queries at a low cost. ### **How It Works** 1. **Dual-Path Ingestion:** The process begins with an n8n Form where you provide a sitemap or individual URLs. The workflow automatically handles XML parsing and URL cleaning to prepare a list of pages for processing. 2. **Clean Content Extraction:** Using **Decodo**, the workflow fetches the HTML of each page and uses a specialized extraction node to strip away code, ads, and navigation, leaving only the high-value text content. **SignUp using:** [dashboard.decodo.com/register?referral_code=55543bbdb96ffd8cf45c2605147641ee017e7900](dashboard.decodo.com/register?referral_code=55543bbdb96ffd8cf45c2605147641ee017e7900). 3. **Vectorization & Storage:** The cleaned text is passed to the **Gemini Embedding** model, which converts the information into 3076-dimensional vectors. These are stored in a **Pinecone** "supportbot" index for instant retrieval. 4. **RAG-Powered Chat Agent:** When a user sends a message through the chat widget, an **AI Agent** takes over. It uses the user's query to search the Pinecone database for relevant business facts. 5. **Intelligent Response Generation:** The AI Agent passes the retrieved facts and the current chat history to **Google Gemini**, which generates a polite, accurate, and contextually relevant response for the user. ### **Requirements** * **n8n Instance:** A self-hosted or cloud instance of n8n. * **Google Gemini API Key:** For text embeddings and chat generation. * **Pinecone Account:** An API key and a "supportbot" index to store your knowledge base. * **Decodo Access:** For high-quality website content extraction. ### **How to Use** 1. **Initialize the Knowledge Base:** Use the Form Trigger to input your website URL or Sitemap. Run the ingestion flow to populate your Pinecone index. 2. **Configure Credentials:** Authenticate your Google Gemini and Pinecone accounts within n8n. 3. **Deploy the Chatbot:** Enable the Chat Trigger node. Use the provided webhook URL to connect the backend to your website's frontend chat widget. 4. **Test & Refine:** Interact with the bot to ensure it retrieves the correct data, and update your knowledge base by re-running the ingestion flow whenever your website content changes. ### **Business Use Cases** * **Customer Support Teams** - Automate answers to 80% of common FAQs using your existing documentation. * **E-commerce Sites** - Help customers find product details, shipping policies, and return information instantly. * **SaaS Providers** - Build an interactive technical documentation assistant to help users navigate your software. * **Marketing Agencies** - Offer "AI-powered site search" as an add-on service for client websites. ### **Efficiency Gains** * **Reduce Ticket Volume** by providing instant self-service options. * **Eliminate Manual Data Entry** by scraping content directly from the live website. * **Improve UX** with 24/7 availability and zero wait times for customers. **Difficulty Level:** Intermediate **Estimated Setup Time:** 30 min **Monthly Operating Cost:** Low (variable based on AI usage and Pinecone tier)

View

Create an all-in-one Discord assistant with Gemini, Llama Vision & Flux images

This n8n template demonstrates how to build **O'Carla**, an advanced all-in-one Discord AI assistant. It intelligently handles natural conversations, professional image generation, and visual file analysis within a single server integration. Use cases are many: Deploy a smart community manager that remembers past interactions, an on-demand artistic tool for your members, or an AI that can "read" and explain uploaded documents and images! ## Good to know * **API Costs:** Each interaction costs vary depending on the model used (Gemini vs. OpenRouter). Check your provider's dashboard for updated pricing. * **Infrastructure:** This workflow requires a separate Discord bot script (e.g., Node.js) to forward events to the n8n Webhook. It is recommended to host the bot using **PM2** for 24/7 uptime. ## How it works 1. **Webhook Trigger:** Receives incoming data (text and attachments) from your Discord bot. 2. **Intent Routing:** The workflow uses conditional logic to detect if the user wants an image (via keyword `gambar:`), a vision analysis (via attachments), or a standard chat. 3. **Multi-Model Intelligence:** * **Gemini 2.5:** Powers rapid and high-quality general chat reasoning. * **Llama 3.2 Vision (via OpenRouter):** Specifically used to describe and analyze images or text-based files. * **Flux (via Pollinations):** Uses a specialized AI Agent to refine prompts and generate professional-grade images. 4. **Contextual Memory:** A 50-message buffer window ensures O'Carla maintains the context of your conversation based on your Discord User ID. 5. **Clean UI Output:** Generated image links are automatically shortened via **TinyURL** to keep the Discord chat interface tidy. ## How to use 1. Connect your **Google Gemini** and **OpenRouter** API keys in the respective nodes. 2. Replace the Webhook URL in your bot script with this workflow's **Production Webhook URL**. 3. Type `gambar: [your prompt]` in Discord to generate images. 4. Upload an image or file to Discord to trigger the AI Vision analysis. ## Requirements * n8n instance (Self-hosted or Cloud). * Google Gemini API Key. * OpenRouter API Key. * Discord Bot Token and hosting environment. ## Customising this workflow O'Carla is highly flexible. You can change her personality by modifying the **System Message** in the Agent nodes, adjust the memory window length, or swap the LLM models to specialized ones like Claude 3.5 or GPT-4o.

View

AI chatbot for Max Messenger with voice recognition (GigaChat +SaluteSpeech)

**Name:** AI Chatbot for Max Messenger with Voice Recognition (GigaChat + Sber) **Description:** ### How it works This workflow powers an intelligent, conversational AI bot for Max messenger that can understand and respond to both **text and voice messages**. The bot uses GigaChat AI with built-in memory, allowing it to remember the conversation history for each unique user and answer follow-up questions. Voice messages are transcribed using Sber SmartSpeech. It's a complete solution for creating an engaging, automated assistant within your Max bot, using Russian AI services. ### Step-by-step * **Max Trigger:** The workflow starts when the **Max Trigger** node receives a new message sent to your Max bot. * **Access Control:** The **Check User** node verifies the sender's user ID against an allowed list. This prevents unauthorized users from accessing your bot. * **Access Denied Response:** If the user is not authorized, the **Access Denied** node sends a polite rejection message. * **Message Type Routing:** The **Text/Attachment** (Switch) node checks if the message contains plain text or has attachments (voice, photo, file). * **Attachment Processing:** If an attachment is detected, the **Download Attachment** (HTTP Request) node retrieves it, and the **Attachment Router** (Switch) node determines its type (voice, photo, or file). * **Voice Transcription:** For voice messages, the workflow gets a Sber access token via **Get Access Token** (HTTP Request), merges it with the audio file, and sends it to **Get Response** (HTTP Request) which uses Sber SmartSpeech API to transcribe the audio to text. * **Input Unification:** The **Voice to Prompt** node converts transcribed text into a prompt, while **Text to Prompt** does the same for plain text messages. Both paths merge at the **Combine** node. * **AI Agent Processing:** The unified prompt is passed to the **AI Agent**, powered by **GigaChat Model** and using **Simple Memory** to retain the last 10 messages per user (using Max `user_id` as the session key). * **Response Delivery:** The AI-generated response is sent back to the user via the **Send Message** node. ### Set up steps Estimated set up time: 15 minutes 1. **Get Max bot credentials:** Visit https://business.max.ru/ to create a bot and obtain API credentials. Add these credentials to **Max Trigger**, **Send Message**, and **Access Denied** nodes. 2. **Add GigaChat credentials:** Register for GigaChat API access and add your credentials to the **GigaChat Model** node. 3. **Add Sber credentials:** Obtain Sber SmartSpeech API credentials and add them to **Get Access Token** and **Get Response** nodes (HTTP Header Auth). 4. **Configure access control:** Open the **Check User** node and change the `user_id` value (currently 50488534) to your own Max user ID. This ensures only you can use the bot during testing. 5. **Customize bot personality:** Open the **AI Agent** node and edit the system message to change the bot's name, behavior, and add your own contact information or links. 6. **Test the bot:** Activate the workflow and send a text or voice message to your Max bot to verify it responds correctly. ### Notes This workflow is specifically designed for Russian-speaking users and uses Russian AI services (GigaChat and Sber SmartSpeech) as alternatives to OpenAI. Make sure you have valid API access to both services before setting up this workflow.

View

👨‍💻

Need Custom Automation?

N8N Automation Expert

Specialized in N8N automation, I design custom workflows that connect your tools and automate your processes.