Abstract
The increasing demand for rapid, high quality social media content necessitates automated multimodal generation systems. This paper presents an advanced multiagent AI driven automated content creation pipeline that transforms technology news into comprehensive multimedia content. The system integrates large language models, image generation models, voice synthesis, research agents, and LangGraph based work flow orchestration with cloud storage automation. Our research objective is to design and evaluate a fully autonomous end-toend pipeline capable of article retrieval, content crawling, script generation, visual asset production, AI image synthesis, voiceover generation, b-roll retrieval, and asset organization. Experimental results demonstrate that the system achieves an average workflow completion time of 6.1 seconds per reel with 37.4% parallel speedup, maintains 93.8% automatic recovery success rate, and produces outputs with semantic coherence. The findings validate the system's potential for scalable automated media production and cross platform publication, while identifying key areas for improving API reliability and content quality assessment.