PR Crisis Detection and Monitoring Workflow

This n8n workflow is designed to automatically monitor and analyze PR-related content for potential crisis signals. It starts with a webhook that receives input data, which could be PR messages or social media posts. The data is then split into manageable chunks using a text splitter node. Each chunk is processed through AI embeddings to encode the text into vector representations, stored in a Redis vector database for efficient similarity search. When new data arrives, the system queries the database for similar past messages to detect patterns or emerging issues. A language model agent, powered by Hugging Face, examines the context and flags potential crises. The analysis results are then logged into Google Sheets for record-keeping and further review. This automated workflow helps PR teams quickly identify and respond to potential reputation crises, saving time and ensuring proactive management across channels.