Route Requests Automatically for Better Performance

Your AI features get faster and more reliable when every request goes to the fastest healthy provider — and quietly retries somewhere else the moment one provider slows down or errors. With NemoRouter you get that automatically: one OpenAI-compatible endpoint that routes on live latency and fails over on its own, so you ship better performance without writing or maintaining a line of failover code.

This is for platform, SRE, and engineering leaders who own the reliability of an AI product. If a single provider hiccup spikes your p95 or returns a wall of 500s to users, the fix isn't more retry glue in every service — it's routing that already knows which provider is healthy right now.

The problem this solves

Pin your app to one provider and you inherit its worst day. Provider regions degrade, models get rate-limited under load, and tail latency swings wildly between vendors for the same prompt. The usual response is defensive code in every service: try Provider A, catch the timeout, fall back to Provider B, track which models are up, tune timeouts by hand. That logic rots, behaves differently in each codebase, and is almost impossible to test against a real outage.

The result is predictable. A regional slowdown at one vendor turns into elevated p95 for your whole product, and a rate-limit wave turns into user-facing errors — even though a perfectly healthy alternative was one HTTP call away.

How it works

NemoRouter sits in front of every provider behind a single endpoint. For each request it picks the fastest qualifying provider based on live latency, and if that provider errors or times out, the request retries on the next healthy one — within the same call, before your user ever sees a failure. You change a base URL; the routing and failover are the gateway's job, not yours.

You also get the latency visibility to prove it's working. Every response carries timing metadata, and your dashboard rolls calls up into p50/p95/p99 so you can watch tail latency by model and provider instead of guessing.

A working example

Point the standard OpenAI SDK at NemoRouter and ask for a latency-optimized route. No fallback code — the retry across providers happens inside the gateway.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.nemorouter.com/v1",
    api_key=key,
)

resp = client.chat.completions.create(
    model="nemo/latency-optimized",
    messages=[{"role": "user", "content": prompt}],
)

print(resp.choices[0].message.content)
print(resp.headers["x-nemo-routed-model"])  # which provider actually served it

If the fastest provider had errored or timed out, that same call would have been served by the next healthy provider — your code path doesn't change, and you can confirm what served it from the response header.

The results

What changes when routing and failover move out of your services and into the gateway. Comparison data verified June 2026.

Latency-aware routing keeps everyday requests on the quickest path, and automatic fallback absorbs the bad moments — both without per-service code, and visible in your p50/p95/p99 metrics. Every feature here is included regardless of plan; the only thing that changes across tiers is the platform fee (0–4%), never the routing or reliability features. (Anthropic, Google, and OpenAI are live today; AWS Bedrock is shipping next.)

Summary

Better AI performance comes from sending each request to the fastest healthy provider and failing over automatically when one degrades — not from more retry code scattered across your services. NemoRouter does both behind one OpenAI-compatible endpoint, then shows the p50/p95/p99 proof in your dashboard. See how the routing modes work in the docs.