A secure LLM-based platform that allows users to upload documents and retrieve precise answers with RAG-powered contextual search and instant clause-level retrieval—reducing legal and enterprise document review time by 75%.
AI-Powered RAG-App for Document Querying NLP & Knowledge Systems — Case Study
A secure LLM-based platform that allows users to upload documents and retrieve precise answers with RAG-powered contextual search and instant clause-level retrieval—reducing legal and enterprise docum
Category
NLP & Knowledge Systems
Industry
LegalTech, Enterprise Knowledge Systems
Key Impact
Reduced document review time by 75%.
Challenge
Large PDF documents made searching for specific clauses or data time-consuming.
Solution
Built a secure upload and LLM-based querying platform that retrieves precise answers from large documents.
Key Achievements
- RAG-powered contextual search
- Instant clause-level retrieval
Tech Stack
- Python
- Flask
- LLMs
- React.js
- Docker
Industry
LegalTech, Enterprise Knowledge Systems
Impact
Reduced document review time by 75%.
Related Services
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Industry Context
Where this project sits in the bigger market picture
AI systems for document review, compliance, clause extraction, and legal operations.
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