Create RAG vector database from Google Drive documents using Gemini & Supabase
Seamlessly transform your static Google Drive folders into a dynamic, searchable brain for your AI agents and chatbots. This workflow automatically extracts text from documents, generates high-quality embeddings with Gemini, and populates a Supabase vector store for instant semantic retrieval. It provides the perfect technical foundation for anyone looking to build a custom knowledge base or advanced RAG system.
Run this with your team's AIWhat This Recipe Does
Manual document processing often creates significant operational bottlenecks, leading to data entry errors and delayed decision-making. This AI Document Extraction automation provides a streamlined solution by transforming unstructured files into organized, actionable data. By integrating Google Drive with a centralized Postgres database, the system automatically identifies, extracts, and categorizes critical information from your documents without manual intervention. This automation is designed to handle high volumes of data through intelligent batch processing, ensuring that even large-scale document migrations or daily intake tasks are completed efficiently. Instead of spending hours copying information from PDFs or spreadsheets, your team can rely on a consistent, automated pipeline that maintains data integrity. By converting this workflow into a Runwork application, business users gain a professional interface to monitor extraction progress and access their structured data immediately. This results in faster turnaround times for financial reporting, contract management, and customer onboarding, ultimately allowing your organization to scale its operations without increasing administrative overhead.
What your team gets
Forms and dashboards, so it is not a script only one person understands
Runs on your schedule in the cloud, so it does not stop when a laptop closes
Endpoints, so the rest of your stack can trigger the same work
Neon Postgres, Google Drive connected for the team, not per person
How It Works
- 1
Open the recipe and connect your accounts
Connect Neon Postgres and Google Drive once, in your team cloud, and nobody has to do it again on their own machine
- 2
Tell your own agent what is different about your process
Claude, ChatGPT, Cursor, whichever your team already uses. It adapts the recipe to how you actually work
- 3
Run it, then leave it running
It lives in your team cloud, so it keeps going after you close the laptop and every teammate's AI can use it
Who Uses This
- Accounts Payable departments use this to automatically extract line items from supplier invoices and sync them with internal financial records.
- Legal and Compliance teams utilize this to scan large volumes of contracts for specific clauses, storing the results in a searchable database for quick retrieval.
- Logistics managers use it to process shipping manifests and delivery receipts, ensuring that inventory data is updated in real-time across the organization.
Frequently Asked Questions
Which file formats can this automation process?
The system is designed to handle common document formats including PDFs, Word documents, and text files stored within your Google Drive folders.
Can I change which specific data points are extracted?
Yes, the extraction logic can be tailored to look for specific fields such as dates, totals, names, or custom identifiers relevant to your business needs.
Do I need a specific database to store the results?
This recipe is configured for Postgres, providing a robust and scalable environment for your structured data, though the destination can be adjusted to other database types.
How does this improve upon manual data entry?
It removes the risk of human error, operates 24/7, and processes documents at a much higher speed than manual input, providing immediate ROI through time savings.
Coming from n8n?
This recipe uses nodes like Langchain.embeddingsGoogleGemini, Langchain.documentDefaultDataLoader, Postgres, Code and 5 more. On Runwork, you don't need to learn n8n's workflow syntax. Describe what you want to your own AI agent in plain English.
Based on n8n community workflow. View original
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Run this with the AI your team already uses
Your agent adapts it, your team cloud keeps it running, and everyone's AI can find it.
Open this recipe in Runwork