Order Shipped Notification Automation

This n8n workflow automates the process of handling ‘Order Shipped’ notifications by capturing webhook requests, processing order details with advanced AI models, storing and querying data in a vector database, and logging the results into Google Sheets. The system also employs a Retrieval-Augmented Generation (RAG) approach to enhance data handling and provides error notifications via Slack, ensuring comprehensive oversight.

The workflow begins with a webhook trigger that listens for incoming POST requests at the ‘order-shipped-notification’ endpoint. The data from these requests is split into manageable chunks by a Text Splitter node. Each chunk undergoes embedding via OpenAI’s language model SDK, which generates vector representations stored in a Supabase vector database.

Subsequently, the data is queried from the database to retrieve relevant vectors, which are then processed through a language model to generate contextual insights or notifications. These insights are appended to a Google Sheets log for record-keeping. Simultaneously, a Slack alert system monitors for errors throughout the process, sending notifications to a designated Slack channel when issues occur.

This automation is particularly useful for e-commerce platforms or order management systems that need to provide real-time updates, maintain logs, and proactively manage errors in order shipment notifications, leveraging AI for intelligent data processing and analysis.