How does an AI gateway improve building AI apps

Building AI applications has become relatively straightforward with minimal coding and access to a model endpoint, but challenges arise when scaling these apps for real-world usage. An AI gateway addresses these challenges by acting as an intermediary between applications and AI model providers, centralizing model access, policies, and telemetry while abstracting provider-specific details. This approach reduces tight coupling, simplifies model access, and enhances reliability by centralizing failure handling and routing logic. Additionally, it provides centralized control to enforce data handling and compliance rules without impeding development speed, and makes cost and observability management more predictable and insightful. Portkey's AI gateway exemplifies these benefits by offering a centralized platform for routing, reliability controls, and observability, allowing platform teams to manage guardrails and policies while application teams focus on product development, making AI a scalable platform capability rather than isolated experiments.