Skip to main content
A conversational chatbot handles a wide range of user messages - greetings, simple FAQs, moderate questions, and occasional complex multi-turn conversations. Most messages are short and simple. Sending all of them to a frontier model wastes 70–80% of your LLM budget. Savings on this workload: typically 60–75% vs Claude Sonnet 4.6 baseline.
SettingValueReason
Tier floorSIMPLEHandles greetings, short Q&A - avoids NANO for public-facing responses
Tier ceilingSTANDARDCaps at Claude Sonnet 4.6 / GPT-5.4 for complex turns
Cost cap$0.005/requestAvoids runaway costs on unexpectedly long conversations
VisionOffUnless users can send images
Tool callingOffUnless the bot calls APIs
Tool qualityAnyOnly relevant if tool calling is on

​
Step 1 - Create the profile

  1. Go to Playground → Configure
  2. Name it Chatbot Production
  3. Set tier floor: SIMPLE, ceiling: STANDARD
  4. Set cost cap: $0.005
  5. Leave Vision and Tool calling unchecked
  6. Click Save & get API key

​
Step 2 - Use the profile key in your app

Replace your existing OpenAI key with the profile key from step 1.

​
Node.js

import OpenAI from "openai";

const client = new OpenAI({
  apiKey:  "sk-routor-YOUR_PROFILE_KEY",
  baseURL: "https://api.routor.io/v1",
});

async function chat(history: { role: string; content: string }[]) {
  const response = await client.chat.completions.create({
    model:    "auto",
    messages: history,
    stream:   true,
  });

  for await (const chunk of response) {
    process.stdout.write(chunk.choices[0]?.delta?.content ?? "");
  }
}

// Multi-turn example
await chat([
  { role: "system",    content: "You are a helpful customer support assistant for Acme Inc." },
  { role: "user",      content: "What are your business hours?" },
  { role: "assistant", content: "We're open Monday–Friday, 9am–6pm EST." },
  { role: "user",      content: "Can I get a refund on an order from last week?" },
]);

​
Python

from openai import OpenAI

client = OpenAI(
    api_key="sk-routor-YOUR_PROFILE_KEY",
    base_url="https://api.routor.io/v1",
)

def chat(history: list[dict]) -> str:
    response = client.chat.completions.create(
        model="auto",
        messages=history,
    )
    return response.choices[0].message.content

history = [
    {"role": "system", "content": "You are a helpful customer support assistant for Acme Inc."},
    {"role": "user",   "content": "What are your business hours?"},
]

reply = chat(history)
history.append({"role": "assistant", "content": reply})
history.append({"role": "user", "content": "Can I get a refund on an order from last week?"})
reply = chat(history)

​
Step 3 - Check routing decisions

After running a few messages, open Dashboard → Overview to see:
  • Which tier each message routed to
  • Cost per request
  • Savings vs baseline
Simple greetings should route to SIMPLE. Refund questions and policy lookups should route to LIGHT or STANDARD. If you’re seeing COMPLEX-tier routing on simple messages, raise the issue in Troubleshooting or test the specific prompt in the Playground.

​
Streaming

For a better user experience, enable streaming to show responses word-by-word. Routor supports streaming identically to the OpenAI API. 
const stream = await client.chat.completions.create({
  model:    "auto",
  messages: history,
  stream:   true,
});

for await (const chunk of stream) {
  const delta = chunk.choices[0]?.delta?.content;
  if (delta) process.stdout.write(delta);
}

​
Cost estimate

On a chatbot handling 10,000 messages/day with a typical mix of short and medium messages:
ScenarioDaily cost
All requests to Claude Sonnet 4.6~$150
With Routor (SIMPLE→STANDARD profile)~$45–60
Savings~$90–105/day
At scale this compounds significantly. A chatbot serving 1M messages/month can save $2,000–3,000/month.