Integrating DevOps and Large Language Model Operations (LLMOps) for GenAI-Enabled E-commerce Innovations A Pathway to Intelligent Automation

This study explores the integration of DevOps methodologies with Large Language Model Operations (LLMOps) to drive intelligent automation and innovation in e-commerce. It is our goal to forecast and examine consumer faith in online marketplaces by making use of GenAI and the neural computation powers of LLMs. The strategy's core goal is to improve confidence by means of a two-pronged approach: first, predictive modeling with LLMs; and second, causal analysis with QCA. In order to determine the degree of trust based on reviews, LLMs examine fundamental aspects of online shopping, such as product quality, customer service, refund policies, and delivery speed. At the same time, customer journey stages including product selection, delivery, and post-purchase assistance are uncovered by QCA as causal linkages between trust. The integration of LLMOps within a DevOps framework ensures efficient deployment and maintenance of AI models, fostering seamless innovation and operational agility. This hybrid approach offers e-commerce platforms actionable insights into enhancing customer trust while setting a benchmark for intelligent automation in the industry.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-30
DOI
https://doi.org/10.5281/zenodo.15183004
Primary Topic
Coral and Marine Ecosystems Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Integrating DevOps and Large Language Model Operations (LLMOps) for GenAI-Enabled E-commerce Innovations A Pathway to Intelligent Automation

Zenodo (CERN European Organization for Nuclear Research)
Coral and Marine Ecosystems Studies
article

Integrating DevOps and Large Language Model Operations (LLMOps) for GenAI-Enabled E-commerce Innovations A Pathway to Intelligent Automation

article en

Abstract

This study explores the integration of DevOps methodologies with Large Language Model Operations (LLMOps) to drive intelligent automation and innovation in e-commerce. It is our goal to forecast and examine consumer faith in online marketplaces by making use of GenAI and the neural computation powers of LLMs. The strategy's core goal is to improve confidence by means of a two-pronged approach: first, predictive modeling with LLMs; and second, causal analysis with QCA. In order to determine the degree of trust based on reviews, LLMs examine fundamental aspects of online shopping, such as product quality, customer service, refund policies, and delivery speed. At the same time, customer journey stages including product selection, delivery, and post-purchase assistance are uncovered by QCA as causal linkages between trust. The integration of LLMOps within a DevOps framework ensures efficient deployment and maintenance of AI models, fostering seamless innovation and operational agility. This hybrid approach offers e-commerce platforms actionable insights into enhancing customer trust while setting a benchmark for intelligent automation in the industry.

Zenodo (CERN European Organization for Nuclear Research)
University College Dublin (IE)
Industry, innovation and infrastructure
Openalex Percentile: Top 59%
Coral and Marine Ecosystems Studies
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Integrating DevOps and Large Language Model Operations (LLMOps) for GenAI-Enabled E-commerce Innovations A Pathway to Intelligent Automation · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS