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RAG & Knowledge Systems
Retrieval-augmented systems that turn your contracts, docs, and knowledge bases into accurate, cited, queryable intelligence.
The Problem
Naive RAG looks fine in a demo but fails on precision: it chunks away context, retrieves the wrong passages, and gives confident wrong answers.
Where We've Applied It
What You Get
- Hierarchical parsing that preserves document structure
- Tuned retrieval with reranking and citations
- Evaluation harness to measure precision and recall
- Source-grounded answers with confidence scoring
Tech Stack
LlamaParseUnstructuredPineconeQdrantRAG
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