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International Scientific Journal of Contemporary Research in

Engineering Science and Management

|ISSN Approved Journal | Impact factor: 7.521 | Follows UGC CARE Journal Norms and Guidelines|
|Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal|Impact
factor 7.521 (Calculated by Google Scholar and Semantic Scholar| AI-Powered Research Tool| Indexing)
in all Major Database & Metadata, Citation Generator

Abstract

UNLOCKING THE POWER OF GENERATIVE AI AGENTS: A FRAMEWORK FOR BUILDING AND DEPLOYING INTELLIGENT, ADAPTIVE, AND GROUNDED SYSTEMS

Raj Nagamangalam, Rajesh Kamisetty

Abstract

Generative AI systems can provide innovative solutions in the business that can increase business practices. Several industries such as manufacturing, finance, and several others are implementing generative AI systems for solving the issues of the customers. Intelligence, adaptive, and data quality are the main principles that can improve generative AI agents. Additionally, the generative AI agent can meet the requirements of the business practices and solve the issues of the entire system. Data quality issues, data security issues, and more can affect the functionality of the grounded system.

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