AutoRAG - Enterprise GenAI Knowledge Retrieval System
A GenAI-powered Retrieval-Augmented Generation (RAG) system designed to enhance real-time document search and summarization for enterprises. The system integrates LangChain, Gemini 1.5 Pro, and Vertex AI for high-speed, accurate knowledge retrieval.
Release date
Feb 8, 2025
Location
New York
Client
Framer
Category
Visual design
01. The Challenge
Enterprises struggled with slow and inefficient document search and knowledge retrieval, making data access time-consuming. A scalable AI-driven system was needed to enhance efficiency.
02. The Solution
A Retrieval-Augmented Generation (RAG) system was developed using Python, LangChain, and Gemini 1.5 Pro to provide real-time document search and summarization. The solution was deployed as a serverless API on Cloud Run, ensuring seamless scalability and high availability.
03. The Result
The system significantly improved knowledge retrieval speed, offering real-time responses and seamless scalability to support 10K+ concurrent users. Continuous fine-tuning via Vertex AI Pipelines enhanced retrieval accuracy over time.