In the realm of enterprise AI, scaling challenges often arise not from the models themselves but from the inference process, leading to increased costs, latency issues, and reliability concerns. While building an in-house inference platform may initially seem like a solution to gain control and avoid vendor lock-in, it often results in significant resource drain and inefficiencies. Purpose-built inference platforms, like the Bento Inference Platform, offer a more effective alternative by providing faster deployment, optimized performance, and enhanced security and compliance, thereby allowing AI teams to focus on innovation rather than infrastructure maintenance. These platforms are designed to streamline deployment, reduce costs, and improve scaling, making them a strategic choice for enterprises that wish to enhance their AI capabilities without compromising on speed or control.