AI Gateway

LiteLLM has been a popular open-source proxy for unifying access to multiple LLM providers behind a single OpenAI-compatible API. Its Python-based SDK and proxy server make it easy to get started, and with support for 100+ providers, it covers a wide range of prototyping and early-stage use cases. However, as

LLM costs compound fast at scale. A single unoptimized prompt chain can multiply expenses by 10x, and without real-time visibility into token usage, teams often discover budget overruns only after the damage is done. As organizations move from AI prototyping to production deployment, a centralized control layer between applications and

TL;DR LLM routers have become essential infrastructure for any team running AI in production. They sit between your application and model providers, handling failover, cost optimization, and unified API access so you don't have to. This article covers the five best LLM router solutions in 2026: Bifrost,

Cloudflare AI Gateway offers a convenient entry point for teams looking to add basic observability and caching to their LLM traffic. But as AI infrastructure requirements grow more complex, many engineering teams are finding that Cloudflare's offering falls short in areas that matter most at scale: multi-provider failover,

TL;DR Helicone is a solid observability-first AI gateway, but teams with demanding production workloads often need more from their routing layer. This article covers five Helicone alternatives worth evaluating in 2026: Bifrost (fastest open-source gateway at 11 µs overhead), LiteLLM (Python-native with the widest provider coverage), Cloudflare AI Gateway

TL;DR Claude Code adoption is surging across enterprise engineering teams, but scaling it beyond a handful of developers creates real operational challenges: runaway costs, zero per-developer spend visibility, and no centralized governance. An enterprise AI gateway solves this by sitting between your Claude Code instances and AI providers, giving