The Middleware Wars: Why Every AI Application Needs an AI Gateway

AI gateways and middleware (Portkey, Helicone, LiteLLM) are becoming essential infrastructure for production AI applications, handling routing, observability, cost management, and fallback across multiple LLM providers.

What AI Gateways Do

• Route requests to cheapest/fastest model
• Monitor costs and latency across providers
• Provide fallback when primary model fails
• Cache responses to reduce API calls
• Enable A/B testing across models

Key Players

• Portkey: Full-featured AI gateway with observability
• LiteLLM: Open source unified LLM interface
• Helicone: LLM observability platform
• Amazon Bedrock: Managed multi-model gateway

Analysis

As companies adopt multiple LLM providers (OpenAI, Anthropic, Google, open source), the need for middleware becomes critical. AI gateways solve a real operational problem: managing the complexity of multi-model deployments. The category is emerging as essential infrastructure, similar to how API gateways became essential for microservices. The winner will be whoever achieves the broadest provider coverage with the lowest overhead.