See llms.txt for all machine-readable content.

Postgres and WhatsApp Business Cloud integration

Save yourself the work of writing custom integrations for Postgres and WhatsApp Business Cloud and use n8n instead. Build adaptable and scalable Development, Data & Storage, workflows that work with your technology stack. All within a building experience you will love.

How to connect Postgres and WhatsApp Business Cloud

Create a new workflow and add the first step

In n8n, click the "Add workflow" button in the Workflows tab to create a new workflow. Add the starting point – a trigger on when your workflow should run: an app event, a schedule, a webhook call, another workflow, an AI chat, or a manual trigger. Sometimes, the HTTP Request node might already serve as your starting point.

Postgres and WhatsApp Business Cloud integration: Create a new workflow and add the first step

Automate restaurant customer service with WhatsApp and Llama AI chatbot

An intelligent WhatsApp-based chatbot designed for restaurants to automate customer interactions related to table bookings, menu inquiries, opening hours, services, and offers. Built using the n8n automation platform and powered by an AI language model, this solution streamlines communication, boosts efficiency, and improves customer satisfaction. Objectives Automate replies to common customer queries on WhatsApp Handle table booking requests with confirmation Provide menu item details, pricing, and dietary information Share restaurant timing, location, and service availability Promote offers and handle promotional queries Operate 24/7 without manual intervention Store bookings and conversations for reporting and analytics Workflow Summary Step 1: Message Reception Node: WhatsApp Trigger (Webhook or API-based) Function: Listens for incoming customer messages. Step 2: Intent Recognition Node: AI Query Processor (e.g., OpenAI API) Function: Detects customer intent (e.g., booking, menu, timing). Step 3: Conditional Routing Node: Switch or IF Node Function: Routes flow based on detected intent: General information (menu, timing, services) Table booking Step 4A: Respond to General Info Queries Node: AI Response or Static Reply Node Function: Returns relevant information (menu, timing, address, etc.). Step 4B: Process Booking Requests Nodes: Collect Booking Details (via chatbot interactions) Store Booking Info (to DB or Google Sheets) Send Booking Confirmation (to customer) Step 5: Context Management Node: Set/Update Customer Data Function: Maintains conversation state and tracks follow-up messages. Database or Google Sheet Columns for Table Booking | Column Name | Description | | ----------------- | ----------------------------------------------- | | reservation\_id | Unique reservation identifier | | guest\_name | Full name of the guest | | contact\_number | Customer’s WhatsApp or mobile number | | email | (Optional) Email address | | booking\_date | Reservation date (YYYY-MM-DD format) | | booking\_time | Reservation time (HH\:MM format) | | party\_size | Number of guests | | table\_id | (Optional) Table number or identifier | | special\_requests | Allergies, seating preferences, etc. | | status | Booking status: Confirmed / Cancelled / Pending | | created\_at | Timestamp when booking was made | | updated\_at | Timestamp when booking was last modified | Prerequisites Verified WhatsApp Business Account with API access n8n instance (Cloud or self-hosted) Access to an AI service (e.g., OpenAI, Claude) Google Sheets, Airtable, MySQL, or other DB integration Setup Instructions Connect WhatsApp API using webhook or third-party WhatsApp provider (e.g., 360Dialog, Twilio). Integrate AI using HTTP Request or OpenAI node for response generation. Create Data Store (Google Sheet, Airtable, or MySQL) with defined booking columns. Design Workflow in n8n with intent detection, conditional logic, and response nodes. Test End-to-End by sending different WhatsApp queries and checking logs and stored data. Example Conversation Customer: “Can I book a table for 2 people tomorrow at 8 PM?” Bot: “Sure. Please provide your name and contact number to confirm the reservation for 2 people at 8:00 PM tomorrow.” \[Booking details are saved, and a confirmation is sent.] Benefits Fully automated customer interaction Supports real-time table reservations Accurate and quick responses Scales without increasing staff effort Operates 24/7 Centralized booking data for analytics Analytics and Reporting Track key performance metrics such as: Number of bookings per day/week Average response time Customer satisfaction scores (via feedback node) Popular menu items or query types Booking conversion rates Security and Compliance End-to-end encrypted WhatsApp messages Role-based access to sensitive data Compliance with data protection regulations (e.g., GDPR) Secure API integrations and storage solutions Conclusion This WhatsApp chatbot serves as a reliable, AI-powered digital front desk for restaurants. Built using n8n and scalable components, it automates customer support, manages bookings, and enhances operational efficiency while offering a seamless customer experience.

Build your own Postgres and WhatsApp Business Cloud integration

Create custom Postgres and WhatsApp Business Cloud workflows by choosing triggers and actions. Nodes come with global operations and settings, as well as app-specific parameters that can be configured. You can also use the HTTP Request node to query data from any app or service with a REST API.

Postgres supported actions

WhatsApp Business Cloud supported actions

Postgres and WhatsApp Business Cloud integration details

Postgres

Postgres

Postgres, or PostgresSQL, is a free, open-source tool that helps you emphasize extensibility and SQL compliance. It is an advanced object-relational database that provides high performance, reliability and feature robustness.

WhatsApp Business Cloud

WhatsApp Business Cloud

The cloud-based version of WhatsApp Business API, WhatsApp Cloud API enables companies and developers to build applications on top of WhatsApp to personalize user experiences and quickly and easily respond to customers.

Save engineering resources

Reduce time spent on customer integrations, engineer faster POCs, keep your customer-specific functionality separate from product all without having to code.

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FAQ about Postgres integrations

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Discover our latest community's recommendations and join the discussions about Postgres and WhatsApp Business Cloud integration.

  • Mikhail Savenkov

    Postgres node IN operator with parameters

    Mikhail Savenkov

    Describe the problem/error/question Postgres node is not working with IN Operator when the parameters is an Array. I suppose that’s because of the sanity checks. E.g. I have a list of some workflows that I’m returning v…

    Open topic
  • Honza Pav

    Passing an array as query parameter in Postgresql

    Honza Pav

    Hello, I have a follow-up question related to a topic that has been discussed but is closed: Postgres use array as a query parameters I want to pass an array into a Postgresql query as a query parameter. Ideally, I woul…

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    Issue with AI Agent not reading full PostgreSQL data

    CrizCJK

    Hello everyone, I’m running into an issue with PostgreSQL in n8n that I can’t figure out. My PostgreSQL database has about 20,000 records of sales and stock data. The problem is that my AI Agent doesn’t seem to read th…

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  • Thạch Vũ Ngọc

    Postgresql Insert error parsing ISO format string

    Thạch Vũ Ngọc

    I using Postgresql Insert node, but it error when column type is timestamp I have the input date in ISO 8601 date string format and I keep getting an error. What is the error message (if any)? Input of Insert node O…

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  • Shazim Ali

    Pass dynamic perameters to postgres_SQL node query

    Shazim Ali

    hi i am new to n8n basically i have build a chat bot, which is created query on the base of question, but sometime AI based queries are failed to give accurate result, so i have created sql function in vector database, t…

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Why use n8n to integrate Postgres with WhatsApp Business Cloud

Handle branching, merging and iteration easily. Pause your workflow to wait for external events.

Re-run single steps to test changes in no time. And pin your data to avoid generating trigger events every time you execute.

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