Retrieval-Augmented Generation (RAG) Knowledge Base

A sophisticated knowledge management system that combines document storage with AI-powered retrieval and generation capabilities.

aiCompleted: 2024-01
Retrieval-Augmented Generation (RAG) Knowledge Base

Project Details

This RAG Knowledge Base system transforms how organizations manage and access their internal knowledge. By combining vector search technology with large language models, the platform enables natural language queries against company documentation, policies, and procedures. The system intelligently retrieves the most relevant information and generates comprehensive, contextually appropriate responses, significantly improving knowledge worker productivity and ensuring consistent access to accurate information.

Client

LegalTech Innovations

Technologies Used

Next.jsFastAPIOpenAI EmbeddingsPineconeLangChainPostgreSQL

Key Features

  • Document processing pipeline with automatic chunking and embedding
  • Semantic search powered by vector database technology
  • AI-assisted response generation with source citations
  • User feedback collection for continuous improvement
  • Integration with existing document management systems
  • Role-based access control for sensitive information

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