Automated Podcast Transcription and Publication Workflow

This n8n workflow automates the process of transcribing, analyzing, and publishing podcast content. It starts with a webhook trigger receiving podcast audio or data, then splits the transcription text into manageable chunks. Using AI language models, it generates embeddings for each chunk and stores these vectors in a Pinecone vector database, enabling efficient semantic search. The workflow incorporates a Retrieval-Augmented Generation (RAG) agent that processes the data for context-aware analysis or summarization. The results are logged into a Google Sheet for record-keeping, and error alerts are sent via Slack. This setup is highly useful for content creators wanting automated podcast management, intelligent indexing, and real-time error notifications.