This n8n workflow streamlines the process of managing and utilizing technology radar data, integrating Google Drive, Google Sheets, Google Docs, MySQL, and Pinecone for vector similarity searches. It automates the extraction, transformation, and storage of technology information, enabling advanced querying with LLM agents for strategic decision-making.
The workflow begins with a scheduled Cron trigger that clears existing data in a MySQL database, ensuring fresh data ingestion. It then downloads documents from Google Drive, transforms spreadsheet data into structured text, and updates Google Docs for better data formatting.
In the data setup stage, the workflow pulls tech radar data from Google Sheets, converts it into rows, and updates vectors in Pinecone to facilitate vector search. This enables the retrieval of relevant data snippets for AI agents. Simultaneously, it transforms spreadsheet data into a MySQL database, allowing structured queries for traditional data analysis.
When a user submits a query via the webhook, the workflow determines whether the query should be handled by a Retrieval-Augmented Generation (RAG) agent or an SQL agent, based on intelligent routing. The selected agent then processes the query, utilizing either vector similarity search or SQL queries, with the results validated through guardrails before delivering a final response.
This comprehensive automation is ideal for organizations seeking dynamic, AI-powered insights into their technology landscape, supporting strategic planning, tech assessment, and knowledge management.
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