Automated Applicant Feedback Processing Workflow

This n8n workflow streamlines the collection, analysis, and logging of applicant feedback to enhance recruitment management. It starts with an HTTP webhook trigger that receives feedback data. The data is then split into individual segments using a text splitter, and embeddings are generated via OpenAI’s model. These embeddings are stored in a Pinecone vector database for efficient retrieval. When needed, the workflow queries similar past feedback to provide context for the current response. A language model (from Anthropic) processes the data, guided by a custom prompt, to generate insightful outputs. The results are logged into a Google Sheet for record-keeping, and any errors in the process trigger alerts on Slack. Practical for HR teams looking to automate feedback analysis, this workflow integrates multiple APIs and AI services for intelligent, real-time feedback management.