FastRouter is the LLM gateway that routes every request to the right model, enforces spend limits before the invoice arrives, and gives engineering teams full cost visibility across 200+ models — through one OpenAI-compatible API.
no credit card · no code changes · 2 months pro included for PH community
FastRouter Insights runs every week on your real traffic and surfaces ranked, evidence-backed cost recommendations, automatically. No dashboard to interpret, no digging required. You see exactly what to change and what it's worth, and nothing is applied without you deciding first.
See how Insights worksMost teams discover their AI spend problem when finance asks a question nobody can answer. FastRouter fixes this at the infrastructure level.
No stitching tools together. FastRouter ships observability, cost control, routing, and governance as one system.
Use
fastrouter/auto
as your model ID and FastRouter picks the most cost-efficient
capable model per request. Opt-in, not a default.
Benchmark cheaper models against your actual prompts with LLM-as-Judge scoring. Know before you commit, not after production breaks.
Evolves your prompts automatically toward quality criteria. Finds improvements your team would not find through manual iteration. Reduces token waste.
Observe mode logs violations without blocking. Validate mode blocks them. PII redaction built in. Works on both inputs and outputs.
Agents never see raw provider keys. Every tool call goes through the vault. Full audit log across the entire agent chain. Auth handled centrally.
Append
:flex
for near-realtime at roughly half the price. Batch Processing for
async workloads. Both stack with prompt caching.
FastRouter is OpenAI-compatible. No new SDKs, no refactoring. Change one line and you have full cost attribution, routing, and governance on every request.
One line change. All existing code keeps working. Every request is now logged, attributed, and measurable.
base_url = "https://api.fastrouter.ai/api/v1"
Each team gets its own key with its own budget cap, rate limit, and audit trail. The dashboard shows spend broken down by team, project, and model in real time.
Alert at 80%. Hard stop at 100%. A runaway agent loop hits a wall instead of running until someone wakes up on Monday morning.
Test cheaper models against your real prompts with LLM-as-Judge scoring before committing. Then route the simple tasks to cheaper models and keep frontier models for what actually needs them.
Three patterns that show up in almost every engineering team before they find a better way.
"We spent $47K on LLM APIs last month. Nobody could tell finance which team or feature drove which chunk of the bill. The invoice arrived as one undifferentiated number."Head of Engineering — B2B SaaS, 300 employees
"A bug in a retry loop ran up thousands of dollars in API calls over a weekend. No hard cap. No alert. Just a very uncomfortable Monday morning conversation."Platform Lead — AI-native startup
"We were routing every request to the frontier model because that is what someone picked six months ago and nobody revisited it. Simple classification running on GPT-5 because it was safe."Staff Engineer — Commerce platform
No credit card. No code changes needed to get started. Includes the full control plane: budget caps, Custom Evals, GEPA Prompt Optimization, MCP Gateway, BYOK, and full request tracing.
200+ models. Zero markup. Built for the engineering team that has noticed the bill growing faster than the value.
no credit card · no code changes · zero markup on api calls