This n8n workflow automates the process of parsing, analyzing, and logging new job applications submitted via a webhook. It is designed to streamline recruitment workflows by efficiently handling incoming applications with AI and vector search technology.
The workflow starts with a Webhook trigger that listens for new job application data. The data is then split into manageable chunks using a Text Splitter node, enabling detailed analysis. Each chunk is processed to generate text embeddings through OpenAI’s embedding model, which are stored in a Pinecone vector database for future similarity searches.
A parallel process queries Pinecone with new data to retrieve relevant context or related previous applications. The retrieved information is then used by an AI-powered RAG (Retrieval-Augmented Generation) agent, which provides a comprehensive analysis or response based on the application data.
The results from the AI model are appended as status updates to a Google Sheet log, allowing easy monitoring of the application review process. If any errors occur, they trigger a Slack alert for immediate attention.
This workflow is ideal for HR or recruiting teams looking to automate their initial screening process, improve data organization, and quickly identify relevant applicant information through AI-powered insights.
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