The rule lives in the system
Availability, pricing and stock rules are enforced by the platform rather than by a person who remembers them.
Systems that shipped, and what they had to survive.
Four systems in different industries — retail commerce, rental commerce, accommodation SaaS and industrial data — chosen because they show the same approach applied to problems that look nothing alike from the outside.
- Domains
- Commerce · Rental · Accommodation · Industry
- Markets
- Switzerland · Türkiye · UK · Australia · Gulf
- Languages
- Türkçe · English · العربية
- Response
- A straight answer on fit within a day
What the four have in common.
Different industries, same shape of problem: a business rule that the software has to hold, under load, without a person watching it.
Integrations are queued, not hopeful
Every cross-system message can be retried, traced and reconciled, because the other side will eventually be down.
Configuration beats deployment
Onboarding a property, a clinic or a price tier is a record in the system, not a release from an engineer.
One engineer accountable
Each of these was architected and built by the same person who then had to keep it running.
What each one was called in for.
None of these started as a greenfield brief. Each started with something that had begun to fail.
A backend that could not take campaign day
Frankenspalter — thousands of orders a day against catalogue indexing and an ERP that also wanted the database.
A rental sold like a product
Dcey — a storefront where the date range had to become part of the transaction, not a note on it.
A platform that had to serve many operators
Hujuzatk — properties, rooms and availability per tenant, with rules in configuration.
Production data nobody could see
DORTEK — PLC signals that stopped at the panel until there was a gateway and a cloud to send them to.
The case studies.
Each one covers the situation, the architecture and what it changed.
Frankenspalter · frankenspalter.ch
A Magento backend for thousands of orders a day, with ERP integration that runs while the store keeps selling.
Read the case study →Dcey · dcey.com.tr
Headless rental commerce: Magento GraphQL under a Next.js storefront built around date ranges.
Read the case study →Hujuzatk · hujuzatk.com
Multi-tenant property booking and management SaaS, where onboarding an operator is a record rather than a deployment.
Read the case study →DORTEK · dortek.com.tr
PLC lines through a gateway into cloud dashboards, feeding the stock and planning decisions behind them.
Read the case study →Questions people ask.
Why are there only four case studies?
Because these four are the ones that can be written about openly and that cover genuinely different problems. Other systems — clinic scheduling, education platforms, watch retail — appear on the main site, and the rest sit under agreements that keep client names unmentioned.
Can you talk about a system like ours before we sign anything?
Yes. The first call is about your system, its constraints and the date — not a pitch. You get a straight answer on fit within a day, and a name to call if it is not me.
Have a complex system to build or scale?
Tell me what you are trying to build, automate or scale. You get a straight answer on fit within a day — and a name to call if it is not me.
- [email protected]
- linkedin.com/in/zakaria-haj-mohamad-87188b11b