Skip to content

Case Study

DriveMind AI

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.

Solo Developer2026
FastAPINext.jsLangGraphLangChainPostgreSQLQdrantGoogle Drive APIOpenAI APIDocker
DriveMind AI answering a question with grounded citations from Google Drive documents

Overview

Problem, solution, and outcome.

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

Curriculum to course, step by step.

Enlarge

Implementation

Key capabilities.

1

Google Drive Integration

Read-only Drive connection for syncing metadata and supported document content.

2

Document Ingestion

Extracts and chunks Google Docs, PDFs, DOCX, and plain text files from Drive.

3

Hybrid Retrieval

Combines full-text search, vector search, metadata filtering, fusion, and reranking.

4

LangGraph Agent Workflow

Routes queries, grades evidence, rewrites weak retrieval, and verifies citations.

5

Source-Backed Answers

Responses include citations linked to retrieved document chunks.

6

Production-Oriented Backend

Built with FastAPI, PostgreSQL, Qdrant, Docker, and modular services.

Technical Notes

Architecture decisions.

Explore more work

View the repository or return to the homepage to explore other backend, automation, and full-stack work.