Pretty screenshots don't tell you whether a team can be trusted with your product. Our case studies show the problem, the options, what we chose and why, the measured result, and what we'd do differently.
Case studies being prepared
To fill · L1 + L2Checkout rebuilt for peak sales
Conversion, load time and errors, before and after.
To fill · All layersAn inherited product, rescued
What we found, what we fixed, and how the client's team took over.
To fill · L3An AI feature shipped into a live product
A measured effect on users or operations.
Published with the client's written approval. Under NDA, we describe the client by sector, size and region, and offer a reference call instead.
| Part | What it answers | Example of the level of detail |
|---|---|---|
| Cross-section | Which layers did the team touch? | Interface and APIs rebuilt; data and hosting reviewed |
| Context | Who was the client and what stage were they at? | “A GCC delivery company, about 200 staff, two in-house engineers” |
| The problem | What was hurting, in the client's words? | “Checkout fails every time we run a sale” |
| Options considered | What else could have worked? | “Patch the old app, or rebuild checkout as its own service” |
| What we chose | Which option, and why? | A one-paragraph reason and a simple diagram |
| Outcome | What changed, measured how, over what period? | Before-and-after figures with dates |
| Do differently | What would we change next time? | One honest paragraph |
| People | Who built it? | Names and photos |
Next step
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