A Generative AI and LLM-Driven Data Fabric Architecture for Real-Time CRM Intelligence and Predictive Sales Forecasting in Salesforce Ecosystems Article Swipe
Priya Nair
,
Vikram Chauhan
,
Anika Deshpande
,
Vasudev Sharma
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.5281/zenodo.17894775
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.5281/zenodo.17894775
Real time customer relationship management intelligence continues to evolve as organizations rely on advanced analytics to drive sales planning, revenue optimization, and customer engagement decisions. This study addresses persistent challenges related to data fragmentation, inconsistent contextualization of CRM information, and the limited adaptability of conventional predictive models within Salesforce environments. The research introduces a generative AI and large language model driven data fabric architecture designed to unify distributed CRM assets, automate semantic enrichment, and enhance predictive sales forecasting accuracy. A mixed methodological approach was adopted, combining architectural modeling, data flow simulation, and empirical evaluation using historical opportunity data, customer interaction logs, and multichannel engagement records. Findings indicate that the proposed model improves context aware forecasting precision, reduces data preparation overhead, and increases interpretability for frontline sales teams by enabling narrative style insights generated through domain tuned language models. The framework demonstrates the potential to streamline CRM operations, enhance cross system interoperability, and support adaptive decision making by integrating knowledge graphs and LLM based reasoning into the Salesforce ecosystem. The study contributes an extensible reference architecture for enterprise CRM analytics and offers a pathway for organizations seeking to modernize sales intelligence processes. The results hold significance for both practitioners and researchers by proving that next generation AI enabled data fabrics can meaningfully strengthen forecasting reliability, reduce operational friction, and support scalable data governance strategies across complex CRM landscapes
Related Topics
Concepts
Computer science
Interpretability
Analytics
Predictive analytics
Knowledge management
Data science
Customer relationship management
Customer engagement
Decision support system
Context (archaeology)
Process management
Artificial intelligence
Business intelligence
Data modeling
Empirical research
Generative model
Architecture
Personalization
Data warehouse
Architecture framework
Adaptability
Big data
Machine learning
Business analytics
Customer intelligence
Data architecture
Contextualization
Revenue
Unstructured data
Information system
Sales management
Service-oriented architecture
Systems architecture
Data-driven
Data analysis
Semantic Web
Metadata
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- article
- Landing Page
- https://doi.org/10.5281/zenodo.17894775
- OA Status
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- OpenAlex ID
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- OpenAlex ID
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https://openalex.org/W7114927953Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.5281/zenodo.17894775Digital Object Identifier
- Title
-
A Generative AI and LLM-Driven Data Fabric Architecture for Real-Time CRM Intelligence and Predictive Sales Forecasting in Salesforce EcosystemsWork title
- Type
-
articleOpenAlex work type
- Publication year
-
2025Year of publication
- Publication date
-
2025-12-11Full publication date if available
- Authors
-
Priya Nair, Vikram Chauhan, Anika Deshpande, Vasudev SharmaList of authors in order
- Landing page
-
https://doi.org/10.5281/zenodo.17894775Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://doi.org/10.5281/zenodo.17894775Direct OA link when available
- Concepts
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Computer science, Interpretability, Analytics, Predictive analytics, Knowledge management, Data science, Customer relationship management, Customer engagement, Decision support system, Context (archaeology), Process management, Artificial intelligence, Business intelligence, Data modeling, Empirical research, Generative model, Architecture, Personalization, Data warehouse, Architecture framework, Adaptability, Big data, Machine learning, Business analytics, Customer intelligence, Data architecture, Contextualization, Revenue, Unstructured data, Information system, Sales management, Service-oriented architecture, Systems architecture, Data-driven, Data analysis, Semantic WebTop concepts (fields/topics) attached by OpenAlex
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