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Voice AI Agents

Voice AI Agents & WhatsApp Assistants

Voice is the most natural interface and the least forgiving one. Every hop adds latency, so I design voice agents around time-to-first-response: real-time transcription, focused LLM reasoning, natural speech synthesis and clear escalation rules. I build on Twilio, Vapi, Retell and the WhatsApp Business API.

At a glance

  • Fewer repetitive calls
  • Always available
  • Clean escalation
  • Every call captured
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Outcomes

What you get from this engagement.

  • 01

    Fewer repetitive calls

    FAQs and status checks resolved without a human.

  • 02

    Always available

    Customers get answers outside business hours.

  • 03

    Clean escalation

    Out-of-scope requests go straight to your team.

  • 04

    Every call captured

    Transcripts and analytics for every conversation.

Deliverables

Scope, made concrete.

  • Call-flow and escalation design
  • Voice agent on Twilio, Vapi or Retell
  • WhatsApp voice-note and chat assistants
  • Whisper speech-to-text and natural TTS (ElevenLabs)
  • Order, booking and CRM integrations
  • Call transcripts and analytics
Use cases

Where it delivers value.

  • Inbound customer support
  • Order status and FAQs
  • Appointment booking
  • WhatsApp voice assistants
  • After-hours coverage

Technology

  • Twilio
  • WhatsApp Business API
  • OpenAI Whisper
  • ElevenLabs
  • Vapi
  • Retell
  • Claude API
  • OpenAI
  • Node.js
  • Python
Proof

Related case studies.

Real systems delivered with this approach, with the constraints and results that came with them.

Customer Support & E-commerce5 stages
  1. 01Call
  2. 02Listen
  3. 03Understand
  4. 04Act
  5. 05Escalate

Stage 1, Call: Inbound phone call. Stage 2, Listen: Speech-to-text. Stage 3, Understand: LLM intent detection. Stage 4, Act: FAQ answers, order lookup. Stage 5, Escalate: Live-agent handoff.

01Voice Support Agent

Voice AI Customer-Support Agent

A conversational voice agent that answers inbound calls, resolves FAQ and order-status questions in natural speech, and hands off to a live agent as soon as a request is out of scope.

Inbound voice channel
Calls
Self-service coverage
FAQ + orders
Escalation path
Live handoff
Read case study
whatsapp · ai-sponsor
24/7
0:14

whisper → “Tonight is hard. Can we talk for a minute?”

0:19

I’m here. Let’s take it one step at a time. What’s on your mind?

prompt cache · input tokens≈90% saved

Illustrative interface · client data never shown
02AI Sponsor

Multi-Channel AI Support SaaS Platform

The backend for a 24/7 AI sponsor that supports people in 12-step recovery over chat and WhatsApp voice. It combines Claude-powered conversations, Stripe subscription billing and a prompt-caching architecture that cut LLM input costs by about 90%.

LLM input-cost reduction
~90%
Chat and voice availability
24/7
Automated test categories
12
Read case study
How we work

A delivery process built for zero surprises.

Clear milestones, working demos every week and measurable quality gates, so you always know what's done, what's next and what it costs.

  1. 01

    Discover

    A free 30-minute call to understand the problem, the data and what success looks like.

    You getClear problem statement and success metrics

  2. 02

    Architect

    A written technical plan: architecture, model and vector-store choices, risks, milestones and a fixed quote.

    You getArchitecture document and milestone plan

  3. 03

    Build

    Iterative delivery in short milestones with working demos, so you see progress every week, not at the end.

    You getWorking increments you can test

  4. 04

    Evaluate & harden

    Measured against an evaluation set, then hardened with guardrails, access control, error handling and load testing.

    You getEvaluation report and test suite

  5. 05

    Deploy & support

    Dockerized deployment to your cloud, documentation and handover, with optional ongoing support and improvement.

    You getProduction system plus documentation

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FAQ

Voice AI Agents: common questions.

Will callers know they are talking to AI?

Transparency builds trust, and in many regions disclosure is expected or required. I design agents that are open about being AI while still sounding natural and helpful.

What happens when the AI cannot help?

Clear escalation rules hand the caller to a live agent, so the AI never traps a customer in a loop.

Can it work on WhatsApp?

Yes. I have shipped WhatsApp pipelines that receive voice notes, transcribe them with Whisper, generate replies and send synthesized voice responses back.

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Free discovery call. You'll leave with a clear view of the architecture, risks and next steps, whether or not we work together. I reply within 24 hours.

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