Agents, LLMs, and Salesforce with Multi-Cloud Provider (MCP)
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V5I3P127Keywords:
Agents, Large Language Models, Salesforce, Multi-Cloud Provider, AI Integration, Cloud Orchestration, CRM Automation, Federated Intelligence, Autonomous WorkflowsAbstract
This research paper explores a three-way convergence of large language models (LLMs), intelligent agent architecture, and the Salesforce ecosystem in the context of a multi-cloud provider (MCP) environment. Considering the modern distributed infrastructure scenario, which is spread out across AWS, Azure, and Google Cloud, the integration of Salesforce with LLM-powered agents is just revolutionary, as it opens up a new universe of possibilities for contextual reasoning, automation, and decision intelligence. The authors explain how AI-powered agents can profoundly change the way the CRM system functions as they become agile, self-learning platforms that are able to automate workflows, produce predictive insights and manage the flow of data effortlessly across different clouds. By placing LLMs at the core of Salesforce operations, companies can know their customers even better through natural language reasoning, instant sentiment understanding, and communication based on the customer's intent, thus surpassing the use of static rule-based logic. What is distinctive about this approach is the construction of a harmonized MCP model where autonomous agents can intercommunicate in different atmospheres, thereby securing, scaling, and enabling interoperability without the performance being affected. The research provides examples of what becomes feasible when LLMs are combined with Salesforce APIs and cloud-native tools; thus, intelligent automation can be done efficiently customer engagement through smart automation is the result of lead nurturing to service case resolution while operational friction is minimized. The major points of the paper uncover significant advances in productivity, data integrity, and cross-platform flexibility. Such high-level research opens the door to questions about the next steps of federated AI governance, ethical data handling, and the evolution of agentic frameworks capable of learning, reasoning, and collaborating within multi-cloud ecosystems, leading to the rise of the enterprise landscape that is more intelligent, connected, and human-centered.
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