AI Gateway

Learn how to reduce LLM cost and latency across production AI systems using semantic caching, intelligent model routing, adaptive load balancing, and gateway-level optimization with Bifrost. LLM API spending doubled from $3.5 billion to $8.4 billion between late 2024 and mid-2025, and 72% of organizations plan

Bifrost provides the enterprise governance layer for Claude Code with virtual keys, hierarchical budgets, audit logs, and MCP tool control at 11µs overhead. Claude Code adoption is accelerating across enterprise engineering teams. The tool runs in developer terminals with full user-level privileges, reading files, executing commands, and connecting to

Claude Code is one of the most capable AI coding agents in production today, but it creates a cost visibility problem that catches engineering teams off guard. Each agentic session triggers dozens of API calls for file operations, terminal commands, and code editing, often using high-cost models like Claude

The best enterprise AI gateways for LLM cost tracking give teams hierarchical budget controls, per-request attribution, and real-time enforcement before overages hit. Here are five worth evaluating. LLM API costs are one of the fastest-growing line items in enterprise technology budgets. A customer support agent handling 10,

Claude Code has become one of the most widely adopted AI coding agents in enterprise engineering organizations. Developers use it to scaffold applications, debug complex codebases, refactor legacy systems, and automate routine engineering tasks directly from the terminal. But scaling Claude Code from a handful of developers to an entire

TL;DR: Compare the top enterprise LLM gateways in 2026 for performance, governance, failover, and multi-provider routing at production scale. Enterprise AI teams in 2026 manage requests across multiple LLM providers simultaneously. A single application might route to OpenAI for conversational tasks, Anthropic for coding, and Google Gemini for