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Afrexai Voice Ai Engine
Skill by 1kalin
skill-install — Terminal
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/1kalin/afrexai-voice-ai-engineOr
Voice AI Agent Engineering — Complete Design, Build & Deploy System
Build production-grade AI voice agents for phone calls, customer service, sales, and automation. Platform-agnostic methodology covering conversation design, voice UX, telephony integration, and scaling.
Phase 1: Voice Agent Strategy & Use Case Selection
Voice Agent Brief
voice_agent_brief:
project_name: ""
business_objective: "" # What outcome does this agent drive?
use_case_type: "" # inbound_support | outbound_sales | appointment_booking | notification | survey | ivr_replacement | concierge | internal_ops
target_audience: "" # Who will talk to this agent?
call_volume_estimate: "" # calls/day expected
avg_call_duration: "" # target minutes
languages: [] # primary + secondary
success_metrics: [] # CSAT, resolution rate, booking rate, etc.
human_fallback: "" # when and how to escalate
compliance_requirements: [] # TCPA, GDPR, PCI, HIPAA, state laws
go_live_date: ""
Use Case Fit Scoring (rate 1-5)
| Factor | Score | Weight |
|---|---|---|
| Conversation predictability | _ | 25% |
| Volume justification (>50 calls/day) | _ | 20% |
| Cost savings vs human | _ | 20% |
| Customer acceptance likelihood | _ | 15% |
| Data availability for training | _ | 10% |
| Regulatory risk (inverse — lower = better) | _ | 10% |
| Weighted Total | /5.0 |
Go threshold: ≥3.5 = strong fit. 2.5-3.4 = pilot first. <2.5 = don't build, use humans.
Best Use Cases (start here)
- Appointment booking/confirmation — structured, high volume, clear success metric
- Order status inquiries — data lookup, short calls, high automation potential
- Payment reminders — outbound, scripted, compliance-manageable
- FAQ/tier-1 support — deflect 60-80% of calls from humans
- Lead qualification — inbound, structured questions, CRM integration
Avoid (not ready yet)
- Complex complaint resolution requiring empathy judgment
- Legal/medical advice calls
- Calls where caller is emotionally distressed
- B2B enterprise sales (relationship-dependent)
- Anything requiring visual context sharing
Phase 2: Platform Selection & Architecture
Platform Comparison Matrix
| Platform | Best For | Pricing Model | Latency | Customization | Self-Host |
|---|---|---|---|---|---|
| Vapi | Rapid prototyping, SMB | Per-minute | ~800ms | Medium | No |
| Retell AI | Customer support | Per-minute | ~600ms | Medium | No |
| Bland AI | Outbound at scale | Per-minute | ~700ms | High | No |
| Vocode | Custom/self-hosted | Open source | Variable | Very High | Yes |
| LiveKit | Real-time, custom UX | Usage-based | ~300ms | Very High | Yes |
| Twilio + Custom | Full control | Per-minute + compute | Variable | Maximum | Partial |
| Daily + OpenAI RT | Cutting edge | Per-minute + tokens | ~500ms | High | No |
Metadata
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Paste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-1kalin-afrexai-voice-ai-engine": {
"enabled": true,
"auto_update": true
}
}
}Safety NoteClawKit audits metadata but not runtime behavior. Use with caution.