AI Document Search & Q&A System with Citations (RAG) by Cayman RodenAI Document Search & Q&A System with Citations (RAG) by Cayman Roden
AI Document Search & Q&A System with Citations (RAG)Cayman Roden
Cover image for AI Document Search & Q&A System with Citations (RAG)
Transform your documents into an intelligent Q&A engine. Upload PDFs, policies, or manuals, ask questions in plain English, and get precise answers with exact source citations -- in under 200ms.
I build custom RAG (Retrieval-Augmented Generation) systems with 94% retrieval precision and 96% citation accuracy, validated by 322 automated tests and industry-standard RAGAS evaluation (0.89 score).
What you get😍 - Production-ready document Q&A system
Web interface for uploading docs and asking questions
Source citations with highlighted passages and page numbers
Hybrid search (keyword + semantic) for maximum recall
Docker deployment with scaling capabilities
Full source code and documentation
Proof points😍 - 94% retrieval precision, 96% citation accuracy
RAGAS evaluation score: 0.89
322 automated tests validating quality
Live demo available for testing
Starting at$700
Duration3 days
Tags
Python
ai search
document qa
knowledge base
rag system
Service provided by
Cayman Roden Palm Springs, USA
AI Document Search & Q&A System with Citations (RAG)Cayman Roden
Starting at$700
Duration3 days
Tags
Python
ai search
document qa
knowledge base
rag system
Cover image for AI Document Search & Q&A System with Citations (RAG)
Transform your documents into an intelligent Q&A engine. Upload PDFs, policies, or manuals, ask questions in plain English, and get precise answers with exact source citations -- in under 200ms.
I build custom RAG (Retrieval-Augmented Generation) systems with 94% retrieval precision and 96% citation accuracy, validated by 322 automated tests and industry-standard RAGAS evaluation (0.89 score).
What you get😍 - Production-ready document Q&A system
Web interface for uploading docs and asking questions
Source citations with highlighted passages and page numbers
Hybrid search (keyword + semantic) for maximum recall
Docker deployment with scaling capabilities
Full source code and documentation
Proof points😍 - 94% retrieval precision, 96% citation accuracy
RAGAS evaluation score: 0.89
322 automated tests validating quality
Live demo available for testing
$700