Context
The challenge
A services firm processed large volumes of documents manually, requiring intelligent extraction and searchable knowledge bases.
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Use CaseProfessional ServicesAI & Knowledge Automation
Use case
AI Document Intelligence System
Deployed RAG-based document search and an internal assistant to automate extraction and Q&A across large document volumes.
~45%
Manual review reduction
Illustrative visualization
<2s
Search response time
Illustrative visualization
Approach
What we built
We built a RAG-based document intelligence system with semantic search, structured extraction, and an internal assistant interface.
Results
Outcomes
What changed for the business after delivery.
- Automated document classification
- Searchable knowledge base
- Internal AI assistant for document Q&A
Deliverables
- Document ingestion & chunking pipeline
- Vector search index
- Structured extraction workflows
- Internal AI assistant UI
Technologies used
- OpenAI API
- Vector database
- Python
- React
- PostgreSQL
- FastAPI
Use Cases
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