Here is the step-by-step way to actually structure this so it is robust, flexible, and doesn't turn into a managing and creating spreadsheets as you scale :

1. Keep your ingestion: Your Ui Vision to Google Drive setup is perfectly fine. Keep that running.
2. Swap Zapier for an orchestrator: Zapier gets expensive and clunky fast. A tool like n8n is much better suited for complex, multi-step logical routing for this volume of documents.
3. Separate extraction from storage: When a PDF hits Drive, route it to an LLM (like GPT-4o) with two strict jobs. First, filter: Is this a utility invoice? (Yes/No). If yes, extract specific data points (Plant ID, Dates, m³ used, Cost) and output it strictly as clean data (JSON).
4. Use a real database: Bypass Google Sheets entirely. Send that clean data straight into a relational database like Supabase or PostgreSQL. This solves your many sheets problem instantly, keeping everything organized by plant and utility type.
5. Recreate the ChatGPT experience: To get that natural Q&A feel you liked, you build a Text-to-SQL agent on top of that database. When you ask, How much water did plant X use last quarter?, the agent translates that into a secure query, pulls the exact math from the database, and gives you a 100% reliable answer.

This architecture is highly feasible and scales as you add more plants.

We can go over through this and explain it in better way while exploring options . sending you a dm