I was spending $1,200/month on AI API calls. When I audited where the money was going, I found that 70% of my requests were going to GPT-4 — for tasks that a much cheaper model could handle just as well.
Email summaries? Doesn't need GPT-4.
Ticket classification? Doesn't need Sonnet.
Extracting a name from text? Definitely doesn't need a $0.03/request model.
The Problem
Most AI apps send every request — even simple ones — to the most expensive model. That's like taking a taxi to your mailbox.
| Task | Without TokenRouter | With TokenRouter |
|---|---|---|
| "Summarize this email" | GPT-4o ($0.03) | Haiku ($0.001) |
| "Classify this ticket" | Claude Sonnet ($0.01) | Flash ($0.0005) |
| "Extract this name" | GPT-4o ($0.02) | Local model ($0.00) |
| "Analyze this contract" | GPT-4o ($0.08) | Stays on GPT-4o ($0.08) |
The Solution
I built TokenRouter — an OpenAI-compatible proxy that sits between your app and your AI provider.
It classifies each request by complexity and routes it to the cheapest model that can do the job:
- Simple tasks (extraction, classification) → cheapest available model
- Medium tasks (summaries, Q&A) → mid-tier
- Complex tasks (legal analysis, coding) → premium model
How It Works
Change one line of code — your base URL:
# Before
client = OpenAI(api_key="sk-...")
# After
client = OpenAI(api_key="sk-...", base_url="https://tokenrouter.jenavus.com/v1")
That's it. Your existing code works unchanged. TokenRouter handles the routing automatically.
Results
- 60% average cost reduction
- Zero quality loss — complex tasks still go to premium models
- Automatic fallback — if a model is down, it switches instantly
- Real-time cost dashboard — see exactly where every dollar goes
Try It Free
We're opening early access to the first 50 teams.
- Free tier: 10K requests/month
- Pro: $49/month unlimited
👉 https://tokenrouter.jenavus.com
Happy to answer questions about the routing algorithm or share more detailed cost breakdowns.
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