Founder · LoopStack AI

Andy Hatcher

Founder & AI Automation Consultant · LoopStack AI Ltd

I started building and configuring PCs in 1985, writing HTML in Notepad before Dreamweaver existed, and optimising for search engines before Google was a verb. Along the way I built recording studios, ran multi-screen trading floors, managed IT infrastructure, developed software across half a dozen languages, and watched AI evolve from academic papers into something that genuinely changes how businesses operate. I founded LoopStack AI to bring all of that experience into one place — building practical automation systems that solve real business problems at fixed prices, with no jargon and no lock-in.

AI Automation PC Hardware Since 1985 Infrastructure & Networking Software Development SEO & Search Optimisation eCommerce & CRM Systems AI Diffusion & LLMs Music Production Recording Studio Design

Book a Free Call with Andy → hello@loopstack.uk

Quick Facts

Building PCs since 1985
SEO for 30+ years (top 10 Google)
Musician for 3 decades · 3 studios built
Software development · HTML to AI
Founded LoopStack AI · 2025
Registered in England & Wales
40+ automations delivered

35 years in technology — the long version

I didn't start my career with a grand plan. I started because technology fascinated me — building PCs in 1985, writing HTML in Notepad before anyone called it "web development", configuring networks when DOS 3.1 was current. Over three and a half decades I've worked across PC hardware, infrastructure, software development, SEO, eCommerce, recording studio design, and AI — disciplines that most people keep in separate boxes. That breadth is exactly what makes building AI automations for real businesses possible: you need to understand the business problem before you can design the technical solution.

Late 1980s –
Early 1990s

Audio Visual Technology

My entry into professional technology was through AV — the world of integrated audio visual systems, presentation technology, and broadcast-adjacent work. Long before "digital transformation" was a phrase anyone used, AV professionals were solving the same fundamental problem: how do you take complex technology and make it work reliably for people who just need to get their job done? I learned to design systems around the human workflow rather than the other way around. That principle has stayed with me ever since. AV also taught me rigorous cable management, signal routing, and systems integration — skills that look different in a modern API pipeline but follow the same logic.

1990s –
2000s

Infrastructure & Networking

As organisations started taking their networks seriously, I moved into infrastructure and networking — designing and building the physical and logical foundations that businesses run on. This included LAN and WAN design, server infrastructure, security architecture, and the painful, unglamorous work of making all of it reliable at scale. I worked through the era of on-premise everything into the early cloud transition, which meant I understood both worlds deeply. When clients today ask whether an AI automation should connect to their on-prem database or their cloud CRM, the question isn't abstract to me. I've designed both ends of that cable.

2000s –
2010s

Software Development & SEO

I spent significant time building software — eCommerce platforms, CRM integrations, custom internal tools, and data pipelines across HTML, Python, PHP, and PHP Hadoop. Alongside development I was deeply involved in search engine optimisation, consistently achieving top 10 Google placements for sites I worked on. SEO taught me something that most developers never learn: understanding what people are actually searching for matters more than how clean your code is. That principle carries directly into how we build AI automations today — if the system doesn't solve the problem the client actually has, the technology doesn't matter.

2010s

IT Management & Leadership

Leadership roles changed how I thought about technology. Managing IT teams and departments means you're no longer the person writing the code or pulling the cable — you're responsible for the outcome, the budget, the team's development, and the board's confidence in your department. You learn quickly that technology is a means, not an end. You also learn how frustrating it is to watch organisations spend heavily on systems that nobody adopts, consultants who deliver decks rather than results, and vendor lock-in that turns a three-year relationship into a decade of dependency. Those frustrations shaped LoopStack's model directly: fixed price, client owns everything, no lock-in.

2010s –
2020s

Digital Transformation

Digital transformation work put everything together. Leading transformation initiatives means understanding business strategy, technology capability, change management, and the human side of adoption simultaneously. I've seen transformation programmes that consumed millions and delivered almost nothing, and I've seen carefully scoped projects that changed how an entire organisation operates. The difference is rarely budget — it's clarity of scope, genuine buy-in, and an honest relationship between the organisation and whoever is building the solution. Every lesson from those years went directly into how LoopStack is structured and how we work with clients.

1990s –
2020s

Music Production & Recording Studio Design

For three decades I was a working musician — multi-instrumentalist, producer, and studio builder. I designed and built three recording studios from the ground up: one analogue, two hybrid analogue-digital. This work taught me acoustics, signal flow, analogue-to-digital conversion, and the kind of systems thinking that only comes from wiring a 48-channel console into a DAW while keeping noise floors below -90dB. Studio design is the most demanding integration work I have ever done — it makes enterprise API pipelines look straightforward. The discipline of diagnosing signal path problems, managing latency, and building systems where every component is optimised for the final output carries directly into how I approach AI automation today.

2025 –
Present

Founding LoopStack AI

By early 2025 it was obvious to me that AI had crossed a threshold. The tools — GPT-4, Claude, Make.com, n8n — had become genuinely capable of solving real business problems at costs that made sense for businesses of all sizes. The barrier wasn't technology anymore. It was finding someone who understood both the AI side and the business operations side, who would actually build the thing rather than just advise about it, and who wouldn't hold the client hostage with proprietary platforms and ongoing dependency. So I built that company: LoopStack AI Ltd, registered in England and Wales, UK-based team, fixed-price projects, full IP transfer to the client on completion.

How I approach every project

Three and a half decades of watching technology projects succeed and fail has given me a short list of things that actually matter. Here's what shapes every engagement:

Map before building

No automation gets designed until I understand the actual workflow — who does what, in what order, what goes wrong, and what the downstream effects are. Automating a broken process just breaks it faster. We fix the process logic first, then automate it.

Build it to last without you

Every system I build is fully documented, handed over with a video walkthrough, and designed so your team can maintain and extend it without needing to come back to me. That's not common in this industry. It should be.

No surprise invoices

Fixed-price means fixed-price. I've been on both sides of hourly billing relationships and they damage trust. You should know what you're spending before the project starts, not discover it at the end of the month.

Ship something real within 48 hours

By the end of your first scoping session, I can have a working first version of your automation running. Not a prototype, not a wireframe — something that actually processes real data. Speed of feedback beats months of planning every time.

Choose the right tool, not the trendy one

I'm not tied to any platform or vendor. If your automation needs Make.com, we use Make.com. If it needs n8n for data sovereignty, we use n8n. If it needs a custom Python pipeline, we build that. The right tool for the job — always.

Plain English throughout

Most of my clients are non-technical founders and operations directors. Every conversation, every document, every handover is in plain English. Technical detail goes in the documentation appendix, not the main briefing.