Published Paper Details:

Rapid evolvement of artificial intelligence has powered innovations in conversational systems, intelligent Automation,and Immersive Training Platforms are enabling new forms of human-AI collaboration. This work presents A Multi-LLM Intelligent Task Execution aPowered Expressive Assistant system that integrates various large language models (LLMs) to enable the delivery of adaptive, multilingual, and context-sensitive interactions while Orchestrate complex workflows by combining natural language processing, multimodal understanding, and robotics automate processes to support dynamic decision-making, process optimization, and personalized guidance. Unlike traditional chatbots, Or single-model solutions, architecture uses the Complementary strengths of multiple LLMs in order to be expressive. Communication and execution of intelligent tasks over various domains. The fields that may be benefited from this are customer care, education, health care, and industrial training, where the assistant does the following: breaks down instructions, thereby automatically generating step-by-step instructions. It will help the accountants to reduce repetitive tasks, improves efficiency and accuracy, and ensures compliance. The work points to the potential of multi-LLM architectures to advance intelligent automation and shape the next generation of more expressive and human-centric AI systems.