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AI Outbound Voice SDR

Outbound voice agent for reactivation calls, appointment confirmations, and lead qualification at scale.

Setup difficulty: advanced
Home ServicesDentalMed Spa
AgenticVoice AgentAutonomous

The Problem

Outbound calling is the highest-conversion channel SMBs almost never use, because it's expensive and reps burn out. AI voice agents (Bland.ai, Vapi outbound) can dial a list of 500 dormant leads in an afternoon, have a real conversation, and only escalate the warm ones to your human team. Call cost is roughly 1/30th of a human SDR, and the agent never has a bad day.

Best For

Med spasDental practicesInsurance agenciesHome service contractorsGyms and studiosB2B service firms

Workflow Steps

1

Define the call objective + success criteria

One objective per campaign. Examples: confirm tomorrow's appointments, reactivate clients who haven't visited in 6 months, qualify recent web form leads. Success = booking, callback agreed, or DNC tagged.

2

Build the call list with consent

Pull from CRM. Confirm prior business relationship and TCPA-compliant consent. Scrub against your DNC list and the national registry. Skip cell numbers if you don't have express written consent.

3

Write the conversation flow

Opening line that names the prior relationship ('Hi, this is Sara from [Practice] — I see it's been about 8 months since your last cleaning'). Branching: interested → book; not now → soft callback; not interested → polite close + DNC tag.

4

Configure compliance guardrails

Auto-detect 'do not call' or 'remove me' phrases and immediately end + tag DNC. Identify as AI if asked. Respect time-of-day calling rules (8am-9pm local).

5

Throttle + monitor in batches

Start with 25 calls/hour. Have a human review the first 50 transcripts before scaling. Watch connect rate, conversation length, conversion %. Kill the campaign if conversion < 2%.

6

Hand off warm leads instantly

On a yes, the agent either books directly via tool call OR triggers an immediate Slack ping + warm transfer to a human while the lead is still hot.

Copy-Paste Templates

Use these templates as-is or customize for your business.

Reactivation Opening Line
Hi, is this [First Name]? Hi [First Name], this is Sara calling from [Practice Name]. I'm an AI assistant — I just wanted to give you a quick call because it's been about [X months] since your last visit and we wanted to check in. Is now a bad time?
DNC Trigger Phrases
Auto-end + tag DNC on any of: 'do not call', 'remove me', 'take me off your list', 'stop calling', 'don't want to be contacted'. Also on profanity directed at the call. Never argue or retry.
Soft-Yes Callback Schema
{
  "name": "schedule_callback",
  "parameters": {
    "lead_id": "uuid",
    "preferred_window": "string (e.g., 'tomorrow afternoon')",
    "callback_owner": "string (rep name or 'next_available')",
    "context_summary": "string (one-line summary of conversation so far)"
  }
}

Orchestration pattern

Single agent with function-calling: one LLM with a defined toolbox (CRM, calendar, knowledge base) decides which tool to invoke at each turn. Easiest to debug; appropriate for most well-scoped SMB workflows.

Learn the agentic glossary →

Failure modes & mitigations

Where this workflow tends to break in production — and what to put in place before you ship it.

TCPA violation from cold dialing

Mitigation: Strict consented-list enforcement; require source-of-consent timestamp in CRM.

Agent argues with DNC requests

Mitigation: Hard regex match on stop phrases — short-circuit before LLM response.

When NOT to Use This

Do not deploy outbound voice AI without explicit prior business relationship and TCPA-compliant consent for the numbers being called. Heavily regulated industries (healthcare PHI, financial advice) require additional review. Do not use for cold prospecting.

30-60-90 Day Implementation Plan

A phased approach to get this workflow running and delivering ROI.

Days 1–30

Foundation

  • Set up core tools and integrations
  • Configure basic workflow automation
  • Test with a small set of real scenarios
  • Train team on new process

Days 31–60

Optimization

  • Review initial results and adjust triggers
  • Add edge case handling
  • Connect additional data sources
  • Measure time saved vs. manual process

Days 61–90

Scale

  • Roll out to full team or all locations
  • Set up monitoring and alerts
  • Document SOPs for the automated workflow
  • Identify next workflow to automate

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