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• 2d
🚀 I’m Open to Work | Automation Expert
What if the repetitive work your team does every day could simply… disappear?
That’s the kind of problem I love solving.
I’m Uzair Ahmad, a 20-year-old CA student and Automation Expert focused on building practical automation systems that connect tools, streamline business processes, and reduce repetitive manual work.
🔧 My core expertise includes:
→ Make.com
→ n8n
→ Zapier
→ API Integrations
→ Webhooks
→ Business Workflow Automation
→ Third-Party Integrations
→ AI-powered Workflows
→ Data & Process Automation
One thing that gives me a unique perspective in automation is my CA background.
Being a CA student has trained me to look at businesses from a process, accounting, data, and control perspective. I naturally think beyond “Can this task be automated?” and focus on questions like:
“Why is this process being done this way?”
“Where are the inefficiencies?”
“What can be automated without compromising accuracy or control?”
This allows me to understand business workflows and requirements, not just the technical side of connecting different tools.
I don’t just build automations.
I focus on understanding the business problem first, then designing a workflow that makes the process faster, more organized, and less dependent on repetitive manual work.
đź’Ľ Currently open to:
• Automation Engineer / Specialist roles
• Workflow Automation projects
• Freelance & contract opportunities
• Business Process Automation projects
• Long-term collaborations
đź”— Portfolio: https://theprobssolvers.github.io/portfolio
đź“© Email: [uzair.ahmad.automation@gmail.com]
đź“ž Phone: +92 370 9337191
If your team is looking to automate repetitive processes, connect different platforms, or build smarter business workflows, let’s connect.
And if you know someone who could benefit from an Automation Expert, a share would mean a lot. 🤝
#OpenToWork #AutomationExpert #Automation #WorkflowAutomation #n8n #MakeCom #Zapier #APIIntegration #Webhooks #BusinessAutomation #AutomationEngineer #AI #NoCode #CAStudent
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Related posts
Can you build a fully automated e-commerce platform with zero monthly SaaS costs? Yes. 🛠️
I just dropped my new case study detailing how I engineered a self-sustaining data architecture for Oz Golden Rush. By combining Framer, Make.com, and Airtable, I automated their entire inventory, dynamic pricing, and social feeds—all wrapped in a custom vector UI.
Take a look at the project to see how I bridged the gap between zero-code automation and frontend engineering!
https://contra.com/p/cEbebMRL-automated-data-architecture-for-oz-golden-rush
Linking inventory changes straight to dynamic pricing removes the manual lag and keeps the storefront responsive.
A system I designed for local service businesses that consistently lose out on Google reviews. Full build in progress
Automated Review Requests for Local Service Businesses
The Problem:
Google reviews are one of the strongest signals for local search ranking, this is well established across HVAC companies, cleaning services, salons, contractors, and landscaping businesses. Every owner in this space knows reviews matter. Very few of them ask for one consistently.
The reason isn't a lack of care, it's a lack of a system. Asking every customer, right after every job, every single time, is a small task with no natural trigger behind it. It depends entirely on someone remembering in the moment, usually right when the business is busiest and least likely to remember. The result is a steady stream of satisfied customers who were never actually asked, and a review count that grows far slower than it should.
The Solutionđź‘Ť
I designed a system that removes the dependency on memory entirely, so a review request goes out every time, without anyone having to think about it.
The moment a job is marked complete in the CRM, the system picks it up automatically. It waits a short period first, so the request doesn't feel rushed or robotic, the customer gets a little time to settle in before being asked. Then it sends a review request by SMS or email.
From there, the system tracks what happens next. If the customer clicks through and leaves a review, that's logged as a win and the process ends there, no further messages, no risk of annoying someone who already did what was asked. If there's no response after a few days, the system sends exactly one follow-up, never more than that, since a second or third nudge tends to do more harm than good. Whatever the outcome, sent, clicked, or reviewed, it's recorded in a tracking sheet, so the business owner always has a clear, accurate picture of where every customer stands.
The result is simple: every completed job gets a consistent, well-timed ask, with no manual list to maintain and no customer slipping through the cracks.
What's Next
The full workflow build, including the architecture and the tools behind it, is going up in the next few days.
That email trigger right after a job finishes should cut out the manual reminder step and keep reviews coming in.
• Oct 6
AI Workflow Architect is now live in the ChatGPT Plugin Directory. 🎉
A lot of businesses know they want to automate more — but the harder question is usually:
What should actually be automated, what needs fixing first, and what should stay human?
That’s what I built AI Workflow Architect to help with.
You can give it a real workflow — client onboarding, approvals, handoffs, internal operations — and it helps identify:
• the main bottleneck
• automation readiness
• missing information
• human responsibilities
• controls and safeguards
• the most important next step
The goal isn’t to automate everything.
It’s to make better decisions about where automation will actually help.
The plugin has now been reviewed and approved and is available publicly in ChatGPT.
If you want to go beyond the initial assessment, I also offer the Complete Automation Blueprint, where I turn the workflow into a structured future-state architecture with ownership, controls, exception paths and an implementation sequence.
AI Workflow Architect — Find what to automate.
“What should stay human” is the right wedge for a ChatGPT plugin — most teams automate the wrong step first. Public directory listing is a nice proof point.