Building production voice AI for an Australian AI company


I build AI voice agents and automation systems that call, qualify, follow up and book. In 60 seconds, at 2am, every time.

  • Python
  • n8n
  • Retell
  • Twilio
  • GoHighLevel
  • Docker
  • AWS
Standing by
00:00

Simulated call · example script

Book a call and hear it live
The problem

You already paid for those leads.

Ads, referrals, listings, SEO. The money is spent before the phone rings. What happens in the next sixty seconds decides whether any of it turns into revenue.

0pm
When your phones stop

Calls after hours, at lunch, and during jobs go to voicemail. Most callers never leave one. They call the next name on the list.

0s
How long you have

Speed-to-lead decides who wins. A lead contacted in the first minute converts far better than one called back tomorrow morning.

0×
How often most follow up

One attempt, then the lead goes cold in a spreadsheet. The deal wasn't lost on price. Nobody chased it.

Client work

Built, delivered, running.

Three systems shipped for paying clients, in their own words.

D
Drew MathewsAI automation
200–300
Leads processed

We were building lead lists manually, and a lot of them went nowhere. Ali built the whole pipeline for us: finding businesses, filtering and qualifying them, then reaching out by text and phone automatically.

We're now processing around 200 to 300 leads, with the system handling the qualification and follow-up without us having to manage every step. It's saved us a lot of manual work, and the review follow-up has honestly become one of the best parts of the whole system.

Lead engine built on Google Maps sourcing, n8n qualification, then SMS and voice outreach with review follow up.

  • n8n
  • Google Maps
  • Twilio
  • Voice
  • SMS
J
JonasEnd-to-end AI system
0%
Routine work automated

I came to Ali with an idea, but not much beyond that. He took it from there and built the whole system: the voice agents, LLM side, backend, and branding.

What impressed me was how much of the process could actually be automated. The system now handles a large part of the workflow automatically, with around 80% of the routine work handled without manual intervention.

Ali also stayed involved after launch and helped improve things instead of just handing it over and disappearing.

Complete AI calling operation: LLM integration, voice agents, branding and the full backend behind it.

  • LLM integration
  • AI voice agents
  • Backend
M
MichaelAI caller system
0
Calls a week
0%
No human needed

The AI caller basically handles what a receptionist would, but it doesn't miss calls. Ali connected Retell with GoHighLevel and Twilio and got the whole thing working properly, not just as a demo.

The system is handling around 10,000 calls a week, with roughly 80% of the calls handled by the AI without needing a human to step in. We got it live quickly, and it's been running reliably since.

AI calling system wired into the CRM. Retell on the conversation, GoHighLevel on the pipeline, Twilio carrying the calls.

  • Retell
  • GoHighLevel
  • Twilio
The builds

Three systems, not thirty screenshots.

My own systems, built to close the specific points where leads leak out.

Demo build

Answers every call, books straight into a live calendar

Picks up on the first ring, qualifies the caller, checks real availability, books the slot, sends confirmation and logs the whole transcript to the CRM. Escalates to a human when it should, and knows when it shouldn't.

  • Retell
  • Cal.com
  • n8n
  • Next.js
AI Inbound Receptionist
Open source

Works a thousand leads without sending one bad email

Self-hosted outreach engine: sources businesses, verifies mailboxes properly, scores them, writes per-prospect copy with an LLM and paces the sending. Stops the sequence the moment someone replies.

  • Python
  • Flask
  • React
  • Playwright
  • SQLite
OutLead
In build

Turns an unanswered call into a booked job in 30 seconds

Call goes unanswered, an SMS lands before the caller has put the phone down, the conversation qualifies them over text and drops the booking into the calendar.

  • n8n
  • Twilio
  • GoHighLevel
Missed-Call Recovery
How I work

Four steps. No mystery.

You always know what happens next, what it costs, and what you own at the end of it.

01
Find the leak

Audit

I map where leads actually escape: missed calls, dead follow-up, slow response, nothing after hours. You keep the map whether or not you hire me.

02
Plug the biggest one

Build

One system, scoped to the largest leak first. Agent, workflows, integrations, guardrails. You see it working before it touches a real customer.

03
Go live safely

Deploy

Behind real rails: call caps, escalation paths, human handoff, full transcript logging. Nothing runs unsupervised on day one.

04
It's yours

Handover

Documented and owned by you. I stay on for tuning if you want it, but the system doesn't stop working if you stop paying me.

ProfileTaking new builds
0Client systemsdelivered, all still running
Currently
Production voice AI, Australian AI company
Based
Pakistan · PKT, UTC+5
Working with
UK · US · Canada
Core stack
Python · n8n · Retell · Twilio · GoHighLevel
Who you’d be working with

I’m Ali Hamza. I build the systems, and I’m the one who answers when they break.

I build AI voice agents and sales automation. It is the plumbing between a lead arriving and a booking appearing in your calendar. Python and n8n underneath, Retell and Twilio on the phone, GoHighLevel or your own CRM at the end of it.

Right now I build production voice AI for an Australian AI company. Outside that I take on a small number of builds directly, for businesses in the UK, US and Canada.

You’re not hiring an agency. There’s no account manager and no team you’ll never meet. You get the person who wrote it.

Next step

Find out what your missed calls are actually costing.

Twenty minutes. I’ll map where your leads are leaking and tell you straight whether it’s worth automating. You keep the map either way.

Prefer to message first? WhatsApp or email.

Working with UK · US · Canada