The blog post discusses the integration of Kong AI Gateway with Cerebras AI infrastructure to efficiently deploy and manage advanced AI voice agents, leveraging large language models (LLMs), speech-to-text (STT), and text-to-speech (TTS) capabilities. Kong AI Gateway offers secure traffic control, policy enforcement, and observability, centralizing functions like proxying and routing while extending its capabilities to generative AI models through its plugin ecosystem. It abstracts complexity by providing a standardized interface for interacting with various AI infrastructures and supports features like Prompt Engineering and Semantic Processing. Cerebras complements this with its high-performance Wafer-Scale Engine (WSE) and AI supercomputing solutions, integrating seamlessly with frameworks like PyTorch and TensorFlow. The combination allows for efficient orchestration of AI voice agents, where audio streams are processed through STT models, interpreted by Cerebras language models, and synthesized back into natural speech via TTS models, all governed by Kong AI Gateway. This integration offers a scalable solution for organizations looking to build and experiment with AI agents, optimizing costs and ensuring compliance across AI traffic.