Self-managed cloud deployments and on-premises infrastructure remain essential for enterprise architecture, especially with the decreasing costs of AI inference thanks to advancements in GPU architectures such as NVIDIA Blackwell Ultra. To unlock the value of this infrastructure, enterprises need easy-to-use AI software platforms that can integrate optimized AI hardware, which is where DataStax AI Platform comes in. Built with NVIDIA AI, this platform offers a complete solution for rapidly prototyping, designing, deploying, and scaling AI applications, including support for the latest NVIDIA Blackwell GPUs. To overcome challenges such as component deployment and data management, DataStax collaborates with NVIDIA and Arize to bring a comprehensive AI platform that includes tools like Langflow for rapid development and deployment of AI agents and workflows, and Arize observability and evaluation platform for improving accuracy in AI apps. The platform also addresses deployment and operationalizing systems with tools to manage CPU and GPU resources running on Kubernetes, including common cloud provider options. DataStax customers use the AI platform to build multi-agent systems that leverage standardization protocols like Model Context Protocol (MCP) to connect to different systems, enabling enterprises to fine-tune models for specific business needs and datasets, and scale up inference workloads for higher throughput. By providing a seamless process of continuous AI system improvement, DataStax AI Platform empowers enterprises to be successful with AI in self-managed environments.