Automated document classification & indexing with LLM
AI/NLP · Document Automation · Backend
The client
A document-heavy enterprise managing large volumes of PDFs, DOCX files and scanned documents across multiple teams and workflows.
Challenge
Documents were categorized and tagged by hand, making search slow, inconsistent and hard to scale. The company had no structured way to organize information and quickly retrieve relevant files.
Scope & features
- Automated document classification
- LLM-based keyword and metadata extraction
- Document type and topic detection
- Semantic search
- Full-text indexing
- Automated folder structuring
- PDF, DOCX and scan processing
- Enterprise knowledge organization
Solution
Built an LLM-powered document processing pipeline that automatically classifies, tags, indexes and organizes files.
Outcome
Document processing time dropped by ~80%, search accuracy improved, and 10,000+ documents were processed in the initial batch.
Tech stack
- Node.js
- Python
- OpenAI API
- LangChain
- Elasticsearch
- AWS S3
~80%
less document processing time
Start with an AI audit
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