"AI Business Process Automation Performance Dataset: Task Completion, Benchmarking, and Low-Code Integration"

"Large language models revolutionize business process automation through intelligent integration frameworks. This paper presents a comprehensive end-to-end architecture for LLM-based business process automation. The architecture integrates low-code platforms with advanced performance benchmarking methodologies. Modern enterprises require automated solutions that bridge technical complexity and business accessibility. Our framework addresses critical challenges in LLM integration within enterprise environments. The proposed architecture demonstrates measurable improvements in process efficiency and system scalability. Performance benchmarking reveals significant advantages over traditional automation approaches. Low-code integration enables rapid deployment and maintenance of LLM-powered business processes. The framework supports diverse enterprise requirements through modular design principles. Theoretical analysis confirms the architecture's design effectiveness across multiple business scenarios."