agent hive

CHATBOTS

Priority IVR callback alert with Slack escalation

Detects high-urgency deflected IVR calls (outage, churn risk, VIP), synthesizes an immediate callback offer.

CategoryChatbots
Enginesim
Difficultyintermediate
Triggerwebhook
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerIVR posts deflected-call webhookHTTP webhook
  • ActionSummarize call and score urgencyOpenAI
  • LogicBranch on high urgency or VIP account
  • ActionSynthesize prompt callback offerElevenLabsElevenLabs
  • ActionPost escalation alert to SlackSlack
  • OutputLog callback intent to Postgres queuePostgreSQLPostgres

What it does

Catches the deflected calls you cannot afford to let sit. It scores each abandoned or callback-requested IVR call for urgency, and when it crosses the bar, it synthesizes a fast callback offer, posts a summarized alert to a Slack channel, and records the intent in Postgres so nothing falls through.

When to use it

Use it when some calls are genuinely time-sensitive — outages, cancellation threats, or VIP accounts — and a normal queue is too slow. Routine calls log quietly; urgent ones page the team within seconds.

How it works

  1. 1The IVR posts a webhook with transcript, caller identity, and account tier.
  2. 2OpenAI summarizes the call and assigns an urgency level with a short reason.
  3. 3A logic branch checks whether urgency is high or the account is VIP.
  4. 4ElevenLabs synthesizes a prompt callback offer for the IVR to play back.
  5. 5High-urgency calls post a summarized alert to a Slack channel for immediate pickup.
  6. 6Every call is logged as a callback row in Postgres for the queue.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect ElevenLabsText-to-speech, voice cloning.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Connect PostgresAny Postgres URL — query, write, migrate.
  6. 6
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  7. 7
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  8. 8
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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