Every industry is at the dawn of a new AI-powered era thanks to the exponential advancements in artificial intelligence. Still, the barrier to entry is high for many IT organizations. New machine learning workloads such as training generative AI models exceed the performance and scale capabilities of traditional enterprise infrastructures. HPC systems based on parallel file systems provide adequate performance but complexity and lack of enterprise features make them difficult for many IT teams to support.

Often when organizations are first exploring their needs for AI infrastructure, the focus is on only one aspect of the AI data pipeline – Model Training. This results in a narrow search for a solution that only fits the needs of one aspect of what is needed. Taking a step back and considering the entire end-to-end AI pipeline, many different requirements emerge that typically require unnecessary movement of data, between systems and regions. The result is complicated and tedious data pipelines where data must be constantly copied from tier to tier to give AI training access to the data it needs.

Enter VAST, a comprehensive AI Data Platform with the performance and scalability for the most demanding AI applications, combined with revolutionary data efficiency technologies that reduce the cost of flash to archive-tier economics. When all data throughout the pipeline is available with high-performance, training and serving workflows are simplified and time-to-insight is reduced.

The VAST Data Platform accelerates your entire AI data pipeline by offering a holistic approach to addressing the needs of today’s data-driven organizations. If desired, its unique features can address any of the individual stages of the pipeline. However, as its purpose is expanded into more stages, the time-to-insight benefits compound, while the amount of infrastructure, and copies of data decreases.