Morphik Core demonstrates three core strengths in enterprise scenarios:
- Scale up treatment capacity::
- Support PostgreSQL/MongoDB and other enterprise-class database backend
- Measured search library that can manage 5 million+ documents
- Ensure query response time <1 second through distributed architecture - Business Rules Adaptability::
- Natural language rule engines can be defined such as提取合同金额条款and other business logic
- Support for dynamic addition of metadata fields (e.g., department/project tags)
- Compliance processing: automatic identification and desensitization of sensitive information - cost-benefit ratio::
- Caching mechanism reduces duplicate computations in 80%
- Open source protocols eliminate license fees
- Managed services to be introduced in the future could further reduce operation and maintenance costs
typical use case::
A financial institution built it using Morphik Core:
1. Automatically parsing 100,000+ annual report PDFs in a pipeline
2. Retrieval system for linked financial data and visualization charts
3. Industry risk analysis model based on knowledge mapping
Overall information processing efficiency increased by 3001 TP3T and labor costs decreased by 451 TP3T.
This answer comes from the articleMorphik Core: an open source RAG platform for processing multimodal dataThe
May not be reproduced without permission:AI productivity tools " Why Morphik Core is right for enterprise level knowledge management?
English 
简体中文 
日本語 
Deutsch 
Português do Brasil