RAG workflow for company documents stored in Google Drive

How it works

1. 1.Trigger the workflow when a user submits a question via chat interface or Google Drive
2. 2.Retrieve and automatically load documents from the connected Google Drive folder
3. 3.Segment text content into smaller chunks using recursive character splitting
4. 4.Convert text chunks into vector embeddings using Gemini's embedding model
5. 5.Query Pinecone vector store to find the most relevant document segments
6. 6.Generate precise answers through an AI agent that combines retrieved context with Gemini's reasoning

Use cases

• Enable instant answers to employee questions about company policies, procedures, and internal documentation
• Reduce manual search time across thousands of files by automating document retrieval and relevance ranking
• Support knowledge management by providing a conversational interface to company documentation

Requirements

• Active access to company Google Drive with read permissions for target folders
• API keys configured for Gemini embeddings, Pinecone vector database, and Google Drive integration
• Company documents available in standard formats such as PDF, Word documents, or plain text files

Service Value

Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.