Top 5 Enterprise AI Gateways to Reduce LLM Cost and Latency

As enterprise LLM spending continues to surge, with 72% of organizations expecting their AI budgets to increase, the infrastructure layer between your application and model providers has become mission-critical. AI gateways solve a growing set of production challenges: fragmented provider APIs, unpredictable outages, runaway token costs, and zero visibility into how models perform at scale.

Choosing the right gateway directly impacts your bottom line and application performance. Here are the top five enterprise AI gateways that help teams cut LLM costs and reduce latency in production.

TL;DR

1. Bifrost by Maxim AI

Platform Overview

Bifrost is an open-source, high-performance AI gateway built in Go by Maxim AI. It unifies access to 15+ providers, including OpenAI, Anthropic, AWS Bedrock, Google Vertex AI, Azure OpenAI, Mistral, and Groq, through a single OpenAI-compatible API. Bifrost was purpose-built for production-grade AI systems where every microsecond of gateway overhead matters.

What sets Bifrost apart is raw performance. In published benchmarks at 5,000 RPS on AWS instances, Bifrost adds just 11 µs of overhead per request, making it effectively invisible in your latency budget. Compared to Python-based alternatives, it delivers 9.5x higher throughput, 54x lower P99 latency, and uses 68% less memory.

Features

• **Automatic Failovers:** Seamless provider failover and adaptive load balancing that routes around throttling and outages without any application-level retry logic.
• **Semantic Caching:** Uses vector embeddings to identify semantically equivalent prompts, returning cached responses in ~5 ms instead of the typical 2-second LLM call.
• **Governance and Budget Management:** Hierarchical cost controls with virtual keys, team-level budgets, rate limiting, and audit trails.
• **Built-in MCP Gateway:** Native Model Context Protocol support for AI agents to access external tools securely.
• **Observability:** Native Prometheus metrics, OpenTelemetry integration, and a web dashboard for real-time cost and error monitoring.
• **Drop-in Replacement:** Migrate existing applications by changing a single line of code.

Bifrost also integrates seamlessly with Maxim's AI evaluation and observability platform, giving teams end-to-end visibility from gateway routing through to production quality monitoring.

Best For

Engineering teams running high-volume LLM traffic in production who need ultra-low latency, robust governance, and full infrastructure control. Get started in under a minute with npx -y @maximhq/bifrost or Docker.

2. Cloudflare AI Gateway

Platform Overview

Cloudflare AI Gateway extends Cloudflare's edge network to AI traffic management. It proxies requests between your application and AI providers, offering observability and cost controls with access to 350+ models across providers like OpenAI, Anthropic, and Google.

Features

• Unified billing across multiple AI providers through a single Cloudflare account
• Edge-native caching and rate limiting to reduce redundant model calls
• Request retries and model fallback for improved reliability
• Real-time analytics for token usage, costs, and error tracking

Best For

Teams already using Cloudflare's ecosystem who want a managed, low-friction gateway with consolidated billing.

3. Kong AI Gateway

Platform Overview

Kong AI Gateway brings Kong's mature API management platform into the AI space, extending its battle-tested gateway with AI-specific plugins for routing, security, and governance across LLM providers.

Features

• Semantic caching, routing, and load balancing for LLM traffic
• PII sanitization across 18 languages and prompt security controls
• MCP gateway with OAuth 2.1 authentication for agentic AI workloads
• Token-based rate limiting and cost analytics

Best For

Enterprises already running Kong for traditional API management who want to extend their existing infrastructure to handle AI traffic.

4. LiteLLM

Platform Overview

LiteLLM is an open-source Python SDK and proxy server providing a unified interface to 100+ LLMs. It standardizes all responses to the OpenAI format, making it popular for Python-heavy environments.

Features

• Support for 100+ providers including OpenAI, Anthropic, Azure, and Ollama
• Built-in cost tracking, budgeting, and spend management per project
• Retry and fallback logic for reliability across deployments
• Integrations with observability tools like Langfuse and MLflow

Best For

Python-centric teams needing quick API unification. Works well for prototyping and moderate-scale deployments, though teams handling high concurrency should validate performance at scale.

5. TrueFoundry AI Gateway

Platform Overview

TrueFoundry offers an AI gateway as part of its broader MLOps platform, combining LLM routing and governance with model deployment, fine-tuning, and GPU orchestration.

Features

• Optimized inference backends (vLLM, TGI, Triton) with GPU orchestration
• SOC 2, HIPAA, and GDPR compliance with VPC and air-gapped deployments
• MCP server management with centralized observability
• Integration with agent frameworks like LangGraph and CrewAI

Best For

Organizations needing a combined MLOps and gateway platform, particularly those managing self-hosted model deployments alongside third-party API access.

Choosing the Right Gateway

The best gateway depends on your production requirements. If raw performance and infrastructure efficiency are top priorities, Bifrost's benchmarked results make it the clear leader. For teams embedded in specific ecosystems, Cloudflare and Kong offer natural extensions of existing infrastructure. LiteLLM provides the fastest path to unification for Python teams, while TrueFoundry suits organizations needing full-stack MLOps alongside gateway capabilities.

As AI workloads scale from experiments to revenue-generating products, the gateway becomes the control plane that determines whether your applications scale reliably or buckle under load. Investing in this layer early pays dividends as you grow.

Ready to get started? Try Bifrost in under a minute, or explore Maxim's full AI quality platform for end-to-end evaluation and observability.