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Build an SMS Triage Bot on Telnyx Edge Compute

#ai #sms #edge #telnyx

Support SMS inboxes are usually a routing problem before they are an AI problem.

Someone asks about billing. Someone else needs technical support. A third person wants to talk to sales. The app has to understand the message, pick the right destination, reply to the customer, and remember what happened.

This TypeScript example does that on Telnyx Edge Compute with the Agent SDK.

Code: https://github.com/team-telnyx/telnyx-code-examples/tree/main/agent-sms-triage-bot

What it builds

agent-sms-triage-bot receives inbound SMS webhooks, classifies each message into one of four topics, looks up the route for that topic, replies by SMS, and stores triage history in durable actor state.

The topics are:

  • billing
  • support
  • sales
  • general

The default route table maps those topics to queue names:

billing -> billing-queue
support -> support-queue
sales   -> sales-queue
general -> general-queue
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The request flow 

Inbound SMS
  -> POST /webhooks/sms
  -> TriageAgent.triage(from, text)
  -> Telnyx AI Inference classifies topic
  -> durable route table lookup
  -> SMS reply
  -> triage history update
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The app uses one TriageAgent actor per inbound number. That actor stores route rules, recent history, total messages, and topic counts.

The main routes

  • POST /webhooks/sms receives Telnyx message.received events
  • POST /debug/triage simulates inbound SMS
  • POST /routes updates the route table
  • GET /routes lists route rules
  • GET /history returns recent triage history
  • GET /debug/state inspects actor state
  • GET /health/liveness and GET /health/readiness provide health checks

The Agent SDK piece

The core class is TriageAgent.

It extends the Agent SDK Agent class and uses durable state for:

  • route table
  • triage history
  • total message count
  • topic counts

The AI classification call uses the Telnyx binding:

const completion = await this.env.TELNYX.ai.openai.chat.createCompletion({
  model: this.env.AI_MODEL || "moonshotai/Kimi-K2.6",
  messages: [
    { role: "system", content: CLASSIFY_SYSTEM_PROMPT },
    { role: "user", content: `Customer message: "${text}"` },
  ],
  max_tokens: 2000,
  temperature: 0.2,
});
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The SMS reply uses the same binding pattern:

await this.env.TELNYX.messages.send({
  from: state.fromNumber || state.phoneNumber,
  to: from,
  text: replyText,
});
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That means the example does not hardcode an API key in application code. Messaging and inference both go through this.env.TELNYX.

Try the debug endpoint

After deploying with telnyx-edge ship, you can test without sending a real SMS:

curl -X POST https://agent-sms-triage-bot-<id>.telnyxcompute.com/debug/triage \
  -H "Content-Type: application/json" \
  -d '{"from":"<customer-number>","to":"<triage-number>","text":"Why was I charged twice this month?"}'
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Example response:

{
  "action": "triaged",
  "from": "<customer-number>",
  "to": "<triage-number>",
  "text": "Why was I charged twice this month?",
  "topic": "billing",
  "route": "billing-queue",
  "confidence": 0.95
}
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Then inspect the actor history:

curl "https://agent-sms-triage-bot-<id>.telnyxcompute.com/history?number=<triage-number>"
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Why this pattern is useful

For a small support workflow, this keeps the first version compact:

  • Telnyx Messaging receives and sends SMS
  • Telnyx AI Inference classifies intent
  • Edge Compute hosts the webhook
  • Agent SDK durable state stores routing memory

You can later replace queue names with real integrations: Slack, Zendesk, Salesforce, email, or an internal queue.

Production notes

Before using this with real customer traffic, I would add:

  • webhook signature verification
  • SMS opt-out and consent handling
  • duplicate webhook idempotency
  • PII redaction and retention controls
  • role-based route updates
  • human review for low-confidence classifications
  • alerting when outbound SMS fails

Resources:

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