Intelligent Revenue Operations Platform Using AI, NLP, and Machine Learning

The intelligent revenue operations platform integrates artificial intelligence, natural language processing, and machine learning to transform fragmented business processes into cohesive, automated workflows. This platform addresses critical challenges in lead management, quote-to-cash processes, and compliance requirements by implementing autonomous company research, intelligent classification algorithms, and adaptive workflow automation. Upon identifying a new lead, the system performs comprehensive research across multiple sources, conducts sophisticated profile analysis, determines appropriate industry classifications, and evaluates transaction behaviors—all without manual intervention. The architecture extends through the entire revenue lifecycle, automating quoting, contract generation, order processing, and revenue recognition while maintaining regulatory compliance. Implementation experiences across SaaS and manufacturing industries demonstrate significant efficiency improvements, enhanced decision-making capabilities, and measurable financial benefits. The system's modular design and integration methodology enable adaptation to diverse organizational contexts while addressing data quality, system integration, and change management challenges

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Publication Details

Journal
International Journal of Computing and Engineering
Published
2025-07-14
DOI
https://doi.org/10.47941/ijce.2939
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
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article

Intelligent Revenue Operations Platform Using AI, NLP, and Machine Learning

Laxmi Narayana Chejarla
International Journal of Computing and Engineering
Impact of AI and Big Data on Business and Society
article

Intelligent Revenue Operations Platform Using AI, NLP, and Machine Learning

Laxmi Narayana Chejarla
article en

Abstract

The intelligent revenue operations platform integrates artificial intelligence, natural language processing, and machine learning to transform fragmented business processes into cohesive, automated workflows. This platform addresses critical challenges in lead management, quote-to-cash processes, and compliance requirements by implementing autonomous company research, intelligent classification algorithms, and adaptive workflow automation. Upon identifying a new lead, the system performs comprehensive research across multiple sources, conducts sophisticated profile analysis, determines appropriate industry classifications, and evaluates transaction behaviors—all without manual intervention. The architecture extends through the entire revenue lifecycle, automating quoting, contract generation, order processing, and revenue recognition while maintaining regulatory compliance. Implementation experiences across SaaS and manufacturing industries demonstrate significant efficiency improvements, enhanced decision-making capabilities, and measurable financial benefits. The system's modular design and integration methodology enable adaptation to diverse organizational contexts while addressing data quality, system integration, and change management challenges

International Journal of Computing and EngineeringVol. 7(8)
University of Central Missouri (US)
Openalex Percentile: Top 80%
Impact of AI and Big Data on Business and Society
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Intelligent Revenue Operations Platform Using AI, NLP, and Machine Learning — Laxmi Narayana Chejarla · International Journal of Computing and Engineering (2025) | TGRS Research Map | TGRS