Latenode

Automate WhatsApp Sales with AI Chatbots and Product Data

This Latenode automation allows users to build a WhatsApp chatbot that acts as a sales agent, providing automated responses to customer inquiries. The chatbot is powered by a product catalog vector store and an AI language model, allowing it to understand and respond to user messages in real-time.

The workflow involves importing a product brochure, extracting the text, creating a vector store, and using the OpenAI language model and a memory buffer to generate relevant responses to WhatsApp users. The chatbot can handle both text messages and non-text messages, with the latter triggering a standard response. This automation is designed for businesses looking to enhance their customer support and sales efforts through a conversational WhatsApp interface.

Updated Apr 6, 2026Est. run: 26sEst. cost: $0.0703
How Latenode estimates time and cost

Latenode bills workflow runs in credits: 1 credit = 30 seconds of processing. Minimum charge per run depends on your plan. Plug-and-Play (PnP) AI nodes are billed separately—each PnP token is $1 USD, charged pay-as-you-go at vendor cost plus a small processing fee, with no API keys required.

Full pricing — how credits work →
Messaging & bots

Workflow preview

What this template does

  • Automates responses to customer inquiries on WhatsApp using a product catalog and AI language model.
  • Enables real-time communication between businesses and customers through the WhatsApp Business API.
  • Imports a product brochure, extracts the text, and creates a vector store for natural language understanding.
  • Utilizes the OpenAI language model and a memory buffer to generate relevant responses to user messages.
  • Handles both text and non-text messages, providing a standardized response for the latter.

How it works

1
Trigger

Listen for WhatsApp Messages

The automation starts by listening for incoming messages from the WhatsApp Business Cloud. This allows the chatbot to receive customer inquiries and start the conversation.

2
Action

Fetch Product Brochure

The automation then fetches the product brochure from a URL, which contains the information about the products or services the chatbot will discuss with customers.

3
Action

Extract Text from Brochure

The automation parses the content of the brochure and extracts the relevant text, which will be used to create a vector store for the product catalog.

4
AI

Create Product Catalog Vector Store

The extracted text from the brochure is used to generate vector embeddings, which are stored in a vector store. This allows the chatbot to understand and respond to customer inquiries based on the product information.

5
Logic

Handle Message Types

The automation determines whether the incoming WhatsApp message is text or a non-text message (e.g., image, video, etc.). Based on the message type, the chatbot will follow the appropriate response path.

6
AI

Respond to Text Message

If the incoming message is text, the chatbot uses the product catalog vector store and the language model to generate a relevant response to the customer's inquiry. This allows the chatbot to provide personalized and informative responses in real-time.

7
Action

Send Response to User

The generated response is then sent back to the customer via the WhatsApp Business Cloud, completing the automated conversation and providing the customer with the necessary information or support.

Setup guide

1

Add WhatsApp Business API credential

In the Latenode Credentials panel, add a new credential for the WhatsApp Business API. Provide the necessary API keys, tokens, or OAuth details to authenticate your WhatsApp Business account.

2

Configure OpenAI credential

In the Latenode Credentials panel, add a new credential for the OpenAI API. Provide your OpenAI API key to enable the AI language model functionality.

3

Set up Supabase connection

In the Latenode Credentials panel, add a new credential for Supabase. Provide the necessary connection details, including your Supabase project URL and API key, to enable the vector store functionality.

4

Add product brochure URL

In the Latenode node settings, configure the HTTP Request node to fetch the product brochure from the provided URL. Ensure the URL is correct and accessible.

5

Map WhatsApp message fields

In the Latenode node settings, map the relevant fields from the incoming WhatsApp message to the corresponding inputs for the AI Sales Agent and other downstream nodes.

Requirements

Create a Supabase account and obtain the project URL and API key to use the Supabase integration for storing product data
Generate an OpenAI API key to use the OpenAI GPT-3 integration for generating responses to user messages
Set up the WhatsApp Business Cloud API by creating a WhatsApp Business API account and obtaining the necessary credentials (e.g., phone number, access token) to integrate with the WhatsApp node
Configure the Apify integration to fetch and extract product information from a brochure or other document, and create a vector store for the product data

FAQ

Common questions about this template

Each run uses credits on your Latenode plan. We charge for processing time (1 credit = 30 seconds). Your actual cost depends on your plan and how long the run takes. See pricing plans for plans and how credits work.

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