AI Gateway

A practical guide to AI guardrails implementation covering prompt injection, PII, content safety, and how Bifrost by Maxim AI enforces policies at the gateway layer. AI guardrails implementation is no longer optional for teams running LLMs in production. With the EU AI Act's high-risk obligations taking effect

Semantic caching for LLMs reduces API cost and latency by serving cached responses to similar queries. Learn how Bifrost makes it production-ready. LLM API bills grow faster than traffic for almost every team that ships a chatbot, a RAG application, or an agent. Users rarely ask the exact same

Claude Opus 4.7 vs Qwen 3.6 compared on benchmarks, pricing, deployment, and agentic performance. Pick the right model (or route both) for your AI stack using Bifrost. On April 16, 2026, two of the most anticipated model releases of the year landed on the same day. Anthropic shipped

Bifrost's interactive prompt playground lets teams build, test, and version prompts inside the AI gateway, then ship committed versions to production with a header. Prompts are the control layer for every LLM application. They shape tone, guardrails, tool selection, and reasoning behavior, yet most teams still manage them

Launch Claude Code, Codex CLI, Gemini CLI, and Opencode through a single Bifrost CLI command. Zero environment variables, automatic MCP integration, unified model access. The Bifrost CLI connects coding agents like Claude Code to your Bifrost AI gateway with one command. Instead of manually configuring base URLs, juggling API keys

Bifrost is the best Claude Code gateway for governing token usage per team, with hierarchical budgets, virtual key scoping, model-tier restrictions, and real-time spend dashboards requiring zero workflow changes. Claude Code charges by API token consumption, and costs vary widely across developers. Anthropic's enterprise data shows