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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM49311
Volume:
9 |
5 |
May 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
In this paper, we introduce the Enterprise Intelligence Pipeline, an automated system designed to extract, verify, and match primary business data using a combination of AI-powered tools and structured rule-based logic. The pipeline leverages natural language processing and a Company Identity Matcher module to enrich minimal input queries with accurate and reliable information. Its modular architecture, orchestrated via Amazon ECS, ensures scalability, traceability, and high data quality across enterprise workflows. The system significantly reduces manual effort, improves data consistency, and integrates seamlessly into broader decision-making platforms. Additionally, it supports real-time data validation and feedback mechanisms, enabling continuous enhancement of data accuracy. With a plug-and-play framework, the pipeline is easily customizable for industry-specific applications. By integrating deterministic rules with probabilistic AI models, it offers a balanced solution that combines precision with adaptability.
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Publication Date
1/5/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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