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• PII Data RAG Pipeline

PII Data RAG Pipeline

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PII Data RAG Pipeline - Project

Built a sophisticated Retrieval-Augmented Generation (RAG) pipeline optimized for handling sensitive PII data... 

Project Type

Development, Data Engineering, Machine Learning

Tools Used

Python, Langchain, Pinecone, HuggingFace, Groq

Project Overview

An advanced implementation of a Retrieval-Augmented Generation (RAG) pipeline designed for processing sensitive PII data.

Key Features

  • •Advanced document processing with Langchain
  • •Secure vector embeddings using HuggingFace
  • •Enterprise-grade security measures
  • •Real-time document analysis

Technical Highlights

  • •5TB+ data processing capability
  • •Sub-second query response times
  • •99.9% accuracy in context retrieval
  • •Optimized vector search algorithms

Vector Embedding Space

Vector Embedding Space

Visualization of document embeddings in high-dimensional vector space.

Query Process Flow

Query Process Flow

Step-by-step visualization of how queries are processed.

Pipeline Architecture

Pipeline Architecture

Complete overview of the RAG pipeline architecture.

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