Abstract: Spectra, rich in the physical and chemical signatures of celestial objects, play a pivotal role in revealing the nature of astronomical bodies and exploring the mysteries of the universe. With the advancement of major spectral survey projects worldwide, we have ushered in an era of spectral data at the tens-of-millions scale. Confronted by the challenges posed by massive spectral datasets, we have designed and developed an artificial intelligence-powered spectral visualization and analysis platform. This platform aims to lower barriers to spectral data utilization while enhancing efficiency in both research and education. Leveraging cutting-edge information technology and machine learning algorithms, the platform integrates multiple functions including user management, data governance, visual analytics, spectral classification, parameter measurement, spectral annotation, and multi-band/multi-modal data integration. Its flexible user role and data management architecture significantly reduce the analytical threshold for massive spectral datasets, accelerating scientific productivity. As a core tool of the National Astronomical Data Center, it supports data processing and scientific output for major projects such as LAMOST (Large Sky Area Multi-Object Fiber Spectroscopy Telescope) and MUST (MUltiplexed Survey Telescope). Simultaneously, its potential to bridge scientific research and education opens new pathways for cultivating innovative talent.