Building your first WhatsApp chatbot
Transform your WhatsApp into a high-performing sales channel by deploying an AI agent that instantly understands your product inventory. This workflow ingests product data into a vector store, enabling the bot to answer customer queries with precision and scale. It is the perfect starting point for businesses wanting to automate lead engagement via the world's most popular messaging platform.
Run this with your team's AIWhat This Recipe Does
This automation transforms WhatsApp into a powerful document processing engine for your business. By integrating AI-driven file extraction with instant messaging, it allows team members or customers to submit documents directly through WhatsApp and receive immediate, structured responses. The workflow automatically detects incoming files, extracts relevant data using advanced parsing logic, and processes that information through your internal systems or external APIs. Instead of manual data entry or switching between multiple platforms, this solution enables real-time document analysis and response. It is particularly valuable for businesses that need to handle high volumes of invoices, identity documents, or application forms while maintaining a seamless communication flow. By automating the extraction and verification process, you reduce human error, accelerate turnaround times, and provide a superior experience for mobile-first users who prefer instant communication over traditional email-based workflows.
What your team gets
Forms and dashboards, so it is not a script only one person understands
Runs on your schedule in the cloud, so it does not stop when a laptop closes
Endpoints, so the rest of your stack can trigger the same work
WhatsAppTrigger, Langchain.lmChatOpenAi, Langchain.memoryBufferWindow, Langchain.toolVectorStore, Langchain.embeddingsOpenAi connected for the team, not per person
How It Works
- 1
Open the recipe and connect your accounts
Connect WhatsAppTrigger and Langchain.lmChatOpenAi once, in your team cloud, and nobody has to do it again on their own machine
- 2
Tell your own agent what is different about your process
Claude, ChatGPT, Cursor, whichever your team already uses. It adapts the recipe to how you actually work
- 3
Run it, then leave it running
It lives in your team cloud, so it keeps going after you close the laptop and every teammate's AI can use it
Who Uses This
- Field agents can upload site photos or reports via WhatsApp to instantly trigger data extraction and office notifications.
- Customer support teams can automate the verification of identity documents or utility bills sent by clients for faster account onboarding.
- Finance departments can allow employees to submit expense receipts via message, which are then automatically parsed and logged into accounting software.
Frequently Asked Questions
What types of files can this automation process?
The system is designed to handle common document formats including PDFs, JPEGs, and PNGs, extracting text and data points automatically.
Do I need a WhatsApp Business API account?
Yes, this automation utilizes the official WhatsApp Business integration to ensure secure and reliable message delivery.
Can I customize the logic for different types of documents?
Absolutely. The workflow includes routing logic that allows you to define different processing steps based on the type of file or message received.
How does the system handle complex data extraction?
The automation uses an extraction node that leverages intelligent parsing to identify specific fields like dates, amounts, and names from your documents.
Coming from n8n?
This recipe uses nodes like WhatsAppTrigger, Langchain.lmChatOpenAi, Langchain.memoryBufferWindow, Langchain.toolVectorStore and 11 more. On Runwork, you don't need to learn n8n's workflow syntax. Describe what you want to your own AI agent in plain English.
Based on n8n community workflow. View original
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Run this with the AI your team already uses
Your agent adapts it, your team cloud keeps it running, and everyone's AI can find it.
Open this recipe in Runwork