Cast AI partners with Hugging Face, enabling users to proxy, route prompts in real-time, and deploy models directly from Hugging Face’s Model Hub. This integration streamlines the process of managing AI workloads, reducing infrastructure complexity and improving cost efficiency.

With this new capability, AI Enabler empowers machine learning teams to:

• Proxy Requests Through AI Enabler – Optimize access to Hugging Face-hosted models by intercepting API requests, enabling prompt caching, and setting cost controls, all to reduce inference costs.

• Intelligent Model Routing – Dynamically manage model metadata, versioning, and deployment routes for Hugging Face models within AI Enabler’s ecosystem.

• One-Click Model Deployment – Deploy models from the Hugging Face Model Hub onto GPU-optimized Kubernetes clusters, leveraging AI Enabler’s cost-aware infrastructure scaling.

Leon Kuperman, CTO at CAST AI said:

Hugging Face has revolutionized open-source AI, and our integration makes it effortless for teams to operationalize these models at scale. This partnership ensures that developers can focus on building AI solutions without worrying about infrastructure bottlenecks.

This integration is available immediately for AI Enabler users. To get started, visit www.cast.ai.

About AI Enabler

AI Enabler is a leading AIOps automation platform that simplifies model deployment, scaling, and cost optimization. By leveraging advanced Kubernetes-based orchestration, AI Enabler ensures efficient and seamless AI model execution.