Document intelligence platform
AI Document Processing · OCR · Auto-Classification · Semantic Search
The client
Finger Beton, a German construction materials manufacturer with 300+ employees and a large archive of technical, operational, policy and regulatory documentation stored across multiple systems and formats.
Challenge
Employees spent hours manually classifying and locating files across fragmented archives. Scanned and paper documents were especially hard to search, increasing the risk of missed information and slowing access to technical and operational knowledge.
Scope & features
- Automated document classification
- OCR for scanned and paper documents
- Metadata extraction
- Semantic content search
- Vector-based indexing
- Technical document processing
- Centralized knowledge repository
- Document type and topic detection
Solution
Built an AI document intelligence platform that automatically classifies, indexes and structures corporate documentation, making scanned and digital files searchable by content and meaning.
Outcome
Document processing time dropped by ~80%, and fragmented archives were consolidated into a single searchable knowledge system.
Tech stack
- Python
- Node.js
- OpenAI API
- LangChain
- Elasticsearch
- PostgreSQL
- AWS S3
- OCR
~80%
less document processing time
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