Voice Note Context Extraction and Storage Workflow

This n8n workflow automates the ingestion and processing of voice note transcripts to extract meaningful context data for future AI tasks. It begins with a webhook trigger that receives voice note data, including title, transcript, and timestamp. The ‘Edit Fields’ node formats this data into a structured JSON for clarity.

Next, an AI-powered language model analyzes the transcript to infer user context, correct transcription errors, and extract significant facts, which are then formatted as plain text. The extracted context data is saved as a text file and stored in a vector database (Milvus) for quick retrieval.

Additional nodes embed the context data into vector representations using OpenAI embeddings, preparing it for efficient similarity searches. The workflow also includes sticky notes for documentation and debugging purposes.

This process is highly useful for applications like personal assistants, customer service bots, or knowledge management systems where capturing, understanding, and referencing user voice data enhances responsiveness and personalization.