Production LLM Gateway with Load Balancing
Deploy a high-availability AI gateway that routes requests across multiple LLM providers with failover, rate limiting, cost tracking, and observability for production workloads.
AI Gateway & Routing
Core gateway layer that handles request routing, provider failover, load balancing, and API key management across multiple LLM providers
Full-featured proxy server supporting 100+ LLM providers with load balancing, fallbacks, rate limiting, and spend tracking out of the box — the most battle-tested open-source AI gateway
Ultra-low-latency gateway (50x faster than LiteLLM) ideal when sub-millisecond routing overhead is critical for high-throughput production workloads
Portkey's blazing-fast gateway with integrated guardrails and semantic caching, strong choice when you need built-in content safety at the routing layer
Smart Routing & Cost Optimization
Intelligent request classification and model selection to route queries to the optimal provider based on complexity, cost, and latency requirements
Observability & Evaluation
Monitor gateway health, track per-request costs, measure latency, and evaluate response quality across all routed providers
Open-source LLM observability platform with detailed tracing, cost tracking, and evaluation — essential for understanding gateway performance and debugging routing decisions
One-line integration for LLM observability with request logging, cost analytics, and rate limiting insights — simpler setup than Langfuse
Arize's AI observability tool with strong evaluation and tracing capabilities, ideal when you need deep performance analysis and drift detection
Safety & Guardrails
Enforce content policies, validate inputs/outputs, and apply guardrails before requests reach providers and after responses return
Adds structural and content validation guardrails to LLM outputs, ensuring responses meet schema and policy requirements before reaching end users
NVIDIA's toolkit for programmable guardrails with dialog management, topical control, and safety checks — stronger for conversational use cases
Local Inference Fallback
Self-hosted model serving as a fallback layer when cloud providers are unavailable or for cost-sensitive low-complexity requests
High-throughput inference engine with PagedAttention for efficient GPU memory use — serves as a reliable self-hosted fallback behind the gateway with OpenAI-compatible API
Simple local model runner for lightweight fallback scenarios, easy to deploy and integrates with LiteLLM as a backend provider