Integrating DevOps and Large Language Model Operations (LLMOps) for GenAI-Enabled E-commerce Innovations A Pathway to Intelligent Automation
Year: 2024
Type: article
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.
Author: Rahul Kalva
Language: English
Topic: AI in Service Interactions
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W6930754659
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