A Scalable Architecture for Intelligent Document Processing in Enterprise Environments Using Machine Learning and Natural Language Processing for Data Insight Generation
Keywords:
Intelligent Document Processing, Natural Language Processing, Machine Learning, Enterprise Architecture, Document Understanding, Data Insights, Scalable SystemsAbstract
The exponential growth of unstructured enterprise data, particularly documents in various formats, demands scalable, intelligent solutions for processing and analysis. This paper proposes a robust architecture for Intelligent Document Processing (IDP), integrating scalable machine learning (ML) and natural language processing (NLP) pipelines for effective data insight generation. The architecture supports multiple document types, leverages cloud-native and containerized microservices, and incorporates model lifecycle management for adaptability across enterprise domains. We evaluate existing approaches and position our system as a modular, automated solution capable of reducing manual document processing costs while improving accuracy and decision-making efficiency.
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Copyright (c) 2024 Maurice Daudet Giono (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
