AI Gateway

As enterprises scale LLM deployments across customer support, code assistants, and autonomous agents, the gap between "AI that works in a demo" and "AI that works at enterprise scale" becomes a serious operational risk. Uncontrolled model access, unpredictable costs, compliance blind spots, and zero visibility into

OpenRouter has become one of the most widely used model aggregation platforms, offering developers a single API key to access hundreds of LLMs with unified billing. For prototyping and experimentation, it delivers genuine value. But as AI teams move from sandbox to production, OpenRouter's managed-only architecture introduces limitations

TL;DR: Multi-model routing is now a core requirement for enterprise AI. Bifrost, open-source LLM gateway, gives engineering teams a single control plane to route intelligently across providers by cost, latency, or capability without rewriting application logic. The Multi-Model Routing Problem Enterprise AI teams rarely run a single model in

LiteLLM has served as the default open-source option for teams looking to unify access across multiple LLM providers. Its Python-based proxy translates API schemas from providers like OpenAI, Anthropic, and AWS Bedrock into a standardized OpenAI-compatible format, making it a practical starting point for prototyping and early-stage development. However, as

Enterprise teams running production AI applications need infrastructure that delivers consistent performance, governance, and reliability at scale. Helicone has established itself as a capable LLM observability platform with gateway capabilities, but organizations with demanding production workloads often encounter limitations around latency performance, enterprise governance, and full lifecycle coverage. This article

The Model Context Protocol (MCP) is rapidly becoming the standard for connecting AI models to external tools, data sources, and APIs. As enterprises adopt agentic AI architectures, having an AI gateway that natively supports MCP tool calling isn't optional, it's foundational. Many teams are discovering that