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Systems that went into production

A selection of engineering work delivered across eCommerce, algorithmic trading and games. Clients are described rather than named, and commercially sensitive detail is kept deliberately general.

Case study 01 — eCommerce & AI

AI automation that lifted profit by 119%

UK eCommerce retailer — AI automation engagement, on-site, 2025–2026.

A long-established retailer with a large, complex catalogue and a listing process that depended almost entirely on manual effort. Every new product meant research, copywriting, image work and data entry — a bottleneck that capped how fast the business could grow online.

I designed and deployed AI-driven automation across the eCommerce operation: product listing optimisation, AI content generation, data processing and workflow orchestration, alongside internal tools and web dashboards for the teams that used them daily. The systems ran in production across multiple departments and contributed to a 119% increase in company profits.

  • Listing pipelineBulk product creation and optimisation with AI-generated, on-brand copy.
  • Internal toolingCustom dashboards and HTML interfaces so non-technical staff could drive the automation.
  • Cross-department rolloutBottlenecks identified with management, then automated one workflow at a time.
Outcome
0%

Increase in company profits

Hours → minutes

Listing and content work compressed by orders of magnitude

Stack

PythonC++LLM APIs ML modelsShopify APIREST APIs HTML/CSSPandas
Case study 02 — Fintech

Algorithmic trading systems built to survive live markets

Venture capital firm — algorithmic trading engagement, remote, 2024–2025.

Automated trading strategies for the MetaTrader platforms, written in MQL4, MQL5 and C++. Trading code is unforgiving: it runs unattended against real money, and a silent failure at 3am is indistinguishable from a bad strategy unless the logging tells you otherwise.

Alongside the strategy logic I built the surrounding infrastructure — robust error handling, structured logging and a backtesting framework — so performance claims could be verified against historical data rather than assumed. AI-powered modules were integrated to sharpen decision accuracy, and I took a project leadership role coordinating delivery against tight deadlines.

  • Backtesting frameworkReproducible historical evaluation before anything touched a live account.
  • Failure-first engineeringError handling and logging designed for unattended overnight operation.
  • Performance optimisationExecution paths tuned where latency and tick-level throughput mattered.
Why this matters to you

Trading systems are the strictest training ground for the habits that make ordinary business software reliable: assume it will fail, log enough to diagnose it, and prove it works with data before claiming it does.

That discipline carries straight over into the automation and integration work AleCodex does today — the systems that quietly run your business at 3am should be built the same way.

Stack

MQL4MQL5C++ MetaTrader 4 / 5AI modulesBacktesting
Case study 03 — Games

Open-world survival systems in Unreal Engine 5

Independent games studio — gameplay engineering, part-time, 2024–2025.

Core gameplay systems for an open-world survival title built in Unreal Engine 5 and Unity — resource gathering, crafting and environmental storytelling, along with bespoke environmental assets. Work ran alongside designers, programmers and 3D artists, keeping a single creative vision intact across disciplines.

Game development imposes constraints most business software never faces: everything has to hold a stable frame rate while dozens of systems run simultaneously. Level design and performance optimisation techniques were applied throughout to keep the experience immersive without the budget blowing out.

  • Gameplay systemsResource gathering, crafting loops and environmental storytelling.
  • Performance budgetsOptimisation work to hold frame rate across a large open world.
  • Cross-discipline deliveryClose collaboration with art and design teams on a shared vision.
Also useful for
  • 3D product configurators and interactive visualisation
  • Simulation, training and visualisation tools
  • Real-time rendering and bespoke 3D assets via Blender
  • Interactive marketing experiences that need to run smoothly

Stack

Unreal Engine 5UnityC++ C#Blender
Case study 04 — Team delivery

Leading a five-person engineering team

The project

Team Software Engineering Project, University of Lincoln, October 2022 – May 2023. A graphical artefact delivered alongside a full technical report, built in Unity with C++ and C#.

The role

Led a team of five through scoping, task allocation and delivery — the communication and time-management side of engineering that decides whether a project lands or drifts.

The result

A polished final product delivered on schedule, applying OOP principles throughout. Part of a degree completed at 2:1 in Computer Science with Games Computing.

Your project next

What would you build if the bottleneck disappeared?

Every project above started as somebody's recurring frustration. Tell me yours and I'll tell you honestly whether software fixes it.

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