Problem
Personal files are scattered across Drive, PDFs, docs, screenshots, and notes. Standard search depends on filenames and exact keywords, making it difficult to retrieve context or supporting evidence.
Case Study
Agentic RAG Knowledge Platform for Google Drive
DriveMind AI is a full-stack assistant that connects to Google Drive, indexes personal documents, and answers questions with grounded citations using hybrid retrieval, vector search, metadata filtering, and LangGraph-based workflows.

Overview
Problem
Personal files are scattered across Drive, PDFs, docs, screenshots, and notes. Standard search depends on filenames and exact keywords, making it difficult to retrieve context or supporting evidence.
Solution
DriveMind AI creates a personal knowledge layer over Google Drive. It syncs metadata, extracts content, chunks documents, generates embeddings, combines keyword and vector retrieval, reranks evidence, and generates source-backed answers.
Outcome
An LLM application demonstrating Drive integration, incremental indexing, hybrid retrieval, and workflow orchestration.
Workflow
Implementation
Read-only Drive connection for syncing metadata and supported document content.
Extracts and chunks Google Docs, PDFs, DOCX, and plain text files from Drive.
Combines full-text search, vector search, metadata filtering, fusion, and reranking.
Routes queries, grades evidence, rewrites weak retrieval, and verifies citations.
Responses include citations linked to retrieved document chunks.
Built with FastAPI, PostgreSQL, Qdrant, Docker, and modular services.
Product
First-run setup and Google Drive connection.
Welcome
EnlargeConnect Drive
EnlargeInitial state
EnlargeRetrieval-backed answers with citations and follow-up suggestions.
Chat with citations
EnlargeFile browser, indexing status, and Drive connection controls.
Knowledge library
EnlargeSettings
EnlargeCitation chips and suggested next questions after a grounded answer.
Sources & follow-ups
EnlargeTechnical Notes
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