Voice AI agents that answer every call, book appointments and never put anyone on hold

An AI that picks up on the first ring, understands the caller, books the appointment and knows when to hand over to a human. I led the backend of exactly this for dental offices across the United States, from the first prototype to live patients.

5-star rated mentor on Udacity

1,000+ students trained

10+ large projects

100+ projects delivered

100% success rate

Who this is for#

Clinics, dental practices, service businesses and SaaS companies that lose customers to unanswered calls, voicemail and busy front desks. If a missed call is a missed booking, an AI receptionist pays for itself quickly: it answers instantly, at 2 a.m. and during the lunch rush, in the same calm tone every time.

It also suits companies that already have a product and want a voice channel on top of it — a phone agent for support, order status, lead qualification or outbound reminders.

What you get#

A production voice agent on your phone number: it greets, understands the intent, asks the right follow-up questions and completes the task (book, reschedule, cancel, answer FAQs, take a message).
Real integrations: appointments land in your calendar or practice software; leads land in your CRM; hand-offs ring a real person with context.
Guardrails: the agent knows what it must not do (no medical advice, no promises outside policy), escalates when unsure, and confirms details back before committing anything.
Observability: transcripts, outcomes, latency and cost per call, plus alerts if the provider degrades.
An evaluation set of real call scenarios that runs on every change, so quality goes up over time instead of drifting.

How I build it#

Discovery (a call). We list the calls you actually receive and decide what the agent should handle, what it should hand off, and what "good" sounds like.
Prototype in days. A first agent on a test number, using your real FAQs and booking rules, so you can hear it and pick holes in it early.
Integration and hardening. Function calling into your systems, interruption handling, edge cases (background noise, accents, people who change their mind mid-sentence), latency and cost tuning.
Go live with monitoring. Gradual rollout — for example after-hours first — with dashboards and a weekly review of the calls the agent found hardest.

Proof#

I currently lead the backend of a real-time voice AI receptionist that answers patient calls for dental offices across the United States, 24/7: it books appointments and answers questions. I took it from nothing to a live platform: the streaming speech-to-text → LLM → telephony pipeline, tool calling that behaves identically across voice platforms (ElevenLabs, Telnyx), benchmarking speech providers (Groq, Azure, Telnyx) to cut cost and latency per call, and the Azure production infrastructure (Kubernetes, PostgreSQL).

Before that I built NLP and MLOps backends at Syntheia.io, where a microservice redesign improved system performance by 30% and cut inference time by 20%.

Stack I typically use#

LiveKit or Twilio/Telnyx for telephony · streaming STT (Groq, Azure, Deepgram) · GPT-4o-class models with function calling · ElevenLabs or Azure voices · FastAPI backends · PostgreSQL · Kubernetes on Azure, AWS or GCP · Grafana for the dashboards.

Where and how I work#

I'm based in Cairo (UTC+2) and work remotely with clients in the United States, Europe and the Middle East. That overlap covers all of Europe's working day and US mornings, and I keep a weekly written update so you always know where the project stands.

Questions people ask

How natural does it sound, and how fast does it respond?

Callers hear a natural voice with sub-second turn-taking, because the pipeline streams speech in and audio out instead of waiting for whole sentences. The agent also handles interruptions, so people can talk over it the way they would with a person.

Which phone system does it work with?

It connects to normal phone numbers through providers like Twilio or Telnyx, so nothing changes for your callers. Existing numbers can be forwarded to the agent, or it can be the first line and transfer to staff.

Can it book into our calendar or practice software?

Yes. The agent calls your tools — a calendar, a practice-management system, a CRM — through function calling, so bookings, cancellations and lookups happen in your real systems, not in a separate list someone has to copy over.

What about languages, including Arabic?

English and Arabic are both possible, including Egyptian and Gulf dialects. I have worked on Arabic speech and NLP specifically, and the models and voices now available make bilingual agents realistic.

How do we know it's working?

Every call is logged with its transcript and outcome. I set up dashboards for answer rate, booking rate and hand-offs, and an evaluation set that runs before every change so a prompt tweak can't quietly break the agent.