Deepgram, a leader in Voice AI, has developed a comprehensive approach to ensure the reliability and performance of its audio models, transforming them from research checkpoints into globally available solutions serving millions of customers. The company emphasizes end-to-end control over both software and hardware, running its own data centers to optimize for maximum performance and reliability, which contrasts with many AI companies that rely heavily on cloud providers. Deepgram's core enterprise runtime, built with Rust, is designed for efficiency, offering flexible deployment options and ensuring high accuracy and low latency. While the cloud remains a significant part of their strategy for handling demand spikes and global deployments, Deepgram's focus on retaining hardware control and optimizing AI inference workloads allows them to deliver exceptional real-time AI performance. Their infrastructure, tailored for the nuances of voice applications, provides a reliable and scalable solution for enterprises integrating Voice AI into their workflows.