Nuclear Document Intelligence Platform
Query and analyze complex nuclear documents using natural language with accurate, citation-backed responses.
- NLP
- Document Processing
- Knowledge Retrieval
- RAG Systems
- RAG
- LLMs
- AWS Bedrock
- Claude 3.5 Sonnet
- Pinecone
- LangChain
- LangGraph
- Streamlit
- python
Project Overview
SleepZero Nuclear is built to simplify how users interact with large volumes of technical nuclear documentation. Instead of manually searching through PDFs and reports, users can ask questions in natural language and instantly receive structured, referenced answers drawn directly from the source material. It supports multiple document formats and ensures all outputs are grounded in actual content.
The system uses a retrieval-first architecture with cloud-based vector storage to ensure fast and scalable access to information. With a multi-agent workflow handling query breakdown, retrieval, and response synthesis, it delivers precise and context-aware insights across highly technical datasets.
Key Capabilities
- Natural language querying over technical documents
- Multi-format document ingestion (PDF, DOCX, TXT, Markdown)
- Retrieval-first pipeline with citation-backed responses
- Scalable vector search using Pinecone
- Interactive document exploration via chat interface