AUTOMATION · WORKFLOWS · DUBAI
I'm Emad Yahya — a systems engineer in Dubai who automates business processes with AI: the repetitive work your team does every day — answering the same questions, drafting the same documents, re-keying the same data — turned into workflows that run themselves, connected to your real business data.
This is shipped work, not a slide deck. My AI Visibility & SEO/GEO Coach SaaS runs multi-step AI pipelines in production, and the same automation thinking runs through the HR, booking and POS systems I have built for Dubai businesses. Eight of my systems are in production right now.
My AI Visibility & SEO/GEO Coach is a full SaaS built on automated AI pipelines: it queries ChatGPT, Gemini and Google about a brand, scores every answer and generates a prioritised action plan — one automated workflow: scan, score, fix, re-scan. Prompt pipelines, scoring logic, dashboards and billing, all designed and built by me.
The same discipline runs through my business systems: an HR platform that replaced paper checklists, email threads and spreadsheets with structured workflows; a booking platform that confirms appointments without a phone call; a pharmacy POS whose live price sync removed the manual re-keying between supplier lists and the till. Automation is not a feature I bolt on — it is how these systems were designed.
Most "AI automation" fails the same way: a clever demo that never touches the systems your team actually uses. I build the other way around — automations connect to your CRM, website, WhatsApp, spreadsheets or POS through APIs, so the output lands where the work already happens.
I build custom on the ChatGPT, Gemini and Claude APIs and also work with enterprise chatbot platforms like Engati — chosen per task, not per hype. Either way the engineering is the same: your data stays in accounts you own, API costs are estimated up front and monitored, and every automated action is logged so you can always see what ran and why.
We do not start with an "AI strategy". We scope the single most repetitive process in your business — the one that eats the most hours — and automate that first, because it pays back fastest. You see a working prototype on your own data within days, so you judge results, not promises.
Then it gets engineered properly: permissions, logging, cost caps and a clean handover. You get a fixed written scope and quote within 24 hours of the brief, and you own what gets built.
It depends entirely on scope — automating one workflow is a very different build from a full multi-step pipeline. Describe the process you want off your team's plate and you get a fixed written quote within 24 hours, with AI API running costs estimated up front so there are no surprises.
The high-volume, rule-shaped ones rather than the judgment-heavy ones: the same customer question arriving over and over, the follow-up that always says roughly the same thing, the report someone rebuilds by hand every week, the enquiry re-typed out of a form and into your CRM. Those pay back first because the AI is doing recall and formatting, not deciding anything. Work that turns on a price, a relationship or a risk stays with a person — the automation prepares the draft, a human still signs it off.
Both, and the workflow decides which. When the automation has to sit inside your own data and systems, I build it directly against the ChatGPT, Gemini and Perplexity APIs — the route the AI pipelines in my SEO/GEO Coach SaaS take in production. When what you need is a standard chatbot on standard channels, an enterprise platform such as Engati gets you there sooner, and I will say so instead of quoting a build. The safeguards are the same on either route: actions are logged, and customer-facing output is queued for approval instead of going out unseen, because a model does get things wrong and you want to catch that before your customer does.
It runs on accounts that belong to you — your hosting, your database, your API keys — not on a shared setup of mine you could lose access to later. Each automation is given reach into only the systems its own workflow needs: a follow-up drafter reads enquiries, it does not hold a key to everything else. Every run writes a log entry, so what the automation looked at and what it did afterwards is something you can check rather than take on trust, and nothing passing through it is used to train public models. How your data is handled is written down and agreed before the build starts.
Good enough to send, because the Arabic is never left to the model alone. A model will write Arabic that is grammatically correct and still lands like a translated English sentence, and customers hear that instantly. So the Arabic an automation works from — its prompts, its templates, its standard replies — comes past me before it goes live, and because every run is logged, the Arabic it actually sent stays readable afterwards instead of vanishing into a chat window. I am a native Arabic speaker and have shipped Arabic-first production software, so that review is done by someone who reads the language rather than trusting the model because it sounded certain. Bilingual English/Arabic workflows are the normal build here, not a special request.
Yes — that is the point. Automations connect to your existing CRM, website, WhatsApp, spreadsheets or POS through APIs, without rebuilding what already works. If a connection is not possible, I tell you before the quote, not after the build.
Emad Yahya — portfolio · emaadyahya4@gmail.com · WhatsApp +971 566 392 647