CHATBOTS

IVR Escalation to Zendesk for Unrecognized Orders

When the voice bot can't find a caller's order, it speaks an apology, captures their callback number, and opens a Zendesk ticket so a human follows up.

CategoryChatbots
Enginesim
Difficultyintermediate
Triggerwebhook
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerProvider posts order number and caller IDHTTP webhook
  • ActionQuery Postgres for matching orderPostgreSQLPostgres
  • LogicConfirm order not found
  • ActionSynthesize apology message via ElevenLabsElevenLabsElevenLabs
  • ActionOpen Zendesk callback ticketZendeskZendesk
  • OutputReturn audio URL to provider for playbackHTTP webhook

What it does

Handles the failure path of an order-status IVR gracefully. When the database lookup returns nothing — wrong number, guest checkout, typo — the bot doesn't dead-end the caller. It speaks a short apology via ElevenLabs and files a Zendesk ticket with the caller's number so an agent can call back.

When to use it

Pair this with any voice deflection setup where some lookups will inevitably miss. Use it when you'd rather convert a failed self-service attempt into a tracked support ticket than drop the caller into a voicemail dead end.

How it works

  1. 1The telephony provider posts the order number and caller ID to the webhook.
  2. 2Postgres is queried for the order.
  3. 3A logic step confirms no matching order exists.
  4. 4ElevenLabs synthesizes a brief "we couldn't find that — an agent will call you back" message.
  5. 5A Zendesk ticket is opened with the caller's number, attempted order ID, and call timestamp.
  6. 6The audio URL is returned to the provider for playback.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect PostgresAny Postgres URL — query, write, migrate.
  3. 3
    Connect ElevenLabsText-to-speech, voice cloning.
  4. 4
    Connect ZendeskTickets, queues, knowledge base.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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