Portfolio RAG

Portfolio RAG Chatbot

Explore my work through AI-powered conversations

RAG Chat
Chat with AI enhanced by retrieval from your portfolio knowledge base
Knowledge Base
Query your portfolio content and project documentation
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Access protected features of the chatbot
RAG System Architecture - Frontend to Lambda Functions to Vector Database
RAG-Powered Portfolio Assistant
An AI chatbot that knows my professional journey inside and out

This production-ready RAG system combines semantic search with Claude AI to provide accurate, contextual responses about my projects, skills, and experience. Built with AWS serverless architecture for cost efficiency and scalability.

Technology Stack

Next.js 15
AWS Lambda
OpenSearch
Claude AI
Cognito
TypeScript

Serverless Architecture

Cost-optimized with Lambda Function URLs

RAG-Enhanced Responses

Contextual answers from portfolio content

Production Security

AWS Cognito authentication & rate limiting

Vector Search

Semantic search across project documentation

Engineering Achievement

Reduced API costs by 60% using Lambda Function URLs instead of API Gateway, while maintaining production-grade security and performance.

About This Portfolio Chatbot

This AI-powered chatbot can answer questions about my projects, skills, and AI workflow methodology. It uses Retrieval-Augmented Generation (RAG) to provide accurate, contextual responses based on my portfolio content.

Technologies

  • Next.js 15 + TypeScript
  • Tailwind CSS + shadcn/ui
  • Vector Database Integration

AI Models

  • Claude (Anthropic)

Features

  • Conversation History
  • Source Attribution
  • Real-time Responses

Created by Simon Cheam