The Client
Stackwave Technologies is a fintech startup founded in Abuja in 2024. They build payment infrastructure for mid-market Nigerian businesses — API-first payment processing, settlement automation, and compliance tooling. By early 2026, they had closed a seed round and were scaling their engineering and product team from four people to fourteen. Their CEO, Fatimah Aliyu, had spent her first two years at the company managing hardware piecemeal — laptops from various vendors, some personal machines brought from home, one desktop shared between two developers who worked different shifts.
The seed round changed what was possible. Fatimah wanted to equip the entire technical team properly and stop losing productivity to mismatched hardware, incompatible peripherals, and the constant IT overhead of managing a heterogeneous device fleet.
The Challenge
The challenge wasn't finding a vendor — it was thinking clearly about what ten people doing different jobs actually need from their machines. Stackwave's team broke into three functional groups:
- Backend engineers (5 people): Node.js, Go, PostgreSQL, Docker, running local microservices stacks — memory-hungry work that benefits enormously from fast RAM and many cores
- Frontend engineers / designers (3 people): React, Figma, browser-based testing across multiple environments — needed large displays and fast local builds
- Product and data (2 people): SQL analytics, Metabase dashboards, spreadsheet work, video calls — capable machines but didn't need developer-tier specs
Fatimah had initially considered buying branded business laptops for everyone — Lenovo ThinkPad or Dell Latitude. We asked her to hold that decision for one conversation before committing.
The Consultation
We made the case for desktops over laptops for this specific team. Stackwave's office in Garki is their primary work location — they are not a remote-first company. Engineers come in daily, plug into monitors, and do focused work. For a team that works primarily at fixed desks, a laptop's portability is not a benefit; it is a cost. You pay more for the same CPU performance in a laptop form factor, get worse cooling (thermal throttling under sustained builds), and end up with more repair complexity when something breaks.
Custom desktops gave us the ability to match specs precisely to workload, standardise the hardware platform for easier IT management, and build in power protection that laptops can't have. We also proposed a 10GbE local network switch so their internal code repositories and Docker image caches could be shared over fast local network rather than repeated over internet bandwidth.
Fatimah agreed. We scoped three machine profiles and a deployment plan that would get all ten machines installed, configured, and on the domain within a two-day window.
The Build
Developer Stations (5 units) — ₦2.6 million each:
- CPU: AMD Ryzen 9 7900X — 12 cores, excellent for parallel compilation and Docker builds
- RAM: 64GB DDR5 — enough to run a full local microservices stack without swapping
- GPU: NVIDIA RTX 3060 12GB — adequate for development, supports multiple displays
- Storage: 2TB NVMe (OS + projects) + 2TB HDD (backups and large data)
- UPS: APC 1500VA per machine
Designer Stations (3 units) — ₦2.1 million each:
- CPU: Intel Core i7-14700 — strong single-core for Figma and browser rendering
- RAM: 32GB DDR5
- GPU: NVIDIA RTX 4060 8GB — smooth Figma, multiple browser environments
- Storage: 1TB NVMe + 1TB HDD
- UPS: APC 1500VA per machine
Product/Data Stations (2 units) — ₦1.4 million each:
- CPU: Intel Core i5-13600K
- RAM: 32GB DDR4
- GPU: NVIDIA RTX 3050
- Storage: 1TB NVMe
- UPS: APC 1000VA per machine
Total fleet cost: ₦20.4 million for 10 workstations, all UPS units, a 10GbE switch, and structured cabling in the Garki office. We managed the Windows 11 Pro activation, joined machines to their Azure AD domain, and handed over to their DevOps lead with a full hardware inventory spreadsheet.
The Result
Stackwave's lead backend engineer told us that local Docker build times dropped from an average of 4 minutes 20 seconds on the old laptop fleet to under 55 seconds on the new machines. Their frontend engineer who had been running Figma on a personal 16GB MacBook Air noticed the most dramatic change — Figma on Windows with 32GB RAM and an RTX 4060 runs without the canvas lag she had attributed to "Figma being slow." It wasn't Figma.
From a business operations standpoint, Fatimah reports that IT incidents that used to occupy their part-time IT manager several hours a week have essentially disappeared. Standardised hardware means standardised troubleshooting. When something does need attention, the fix applies to every machine in the same class.
Key Takeaway
For office-based technical teams, custom desktops are almost always the more cost-effective choice over branded business laptops at comparable specs. The performance-per-naira advantage is significant, the cooling advantage under sustained loads is real, and the standardisation benefit for IT management compounds over time. The right question is not "laptop or desktop?" but "what does this person actually do all day, and what hardware serves that work best?"
Are you scaling a technical team in Nigeria? Talk to our team about a fleet deployment — we handle everything from spec to installation.