Services
Four practices.
One team behind all of them.
We do not subcontract and we do not staff projects with people you have not met. The engineers who scope your work are the ones who build it.
Typical timeline
10–20 weeks from kick-off to production
01
Custom software development
Most of our work starts with a spreadsheet or a fifteen-year-old system that nobody wants to touch. We map the workflow with the people who use it every day, replace it in stages so operations never stop, and leave your team with a system they can extend.
What's included
- 01Discovery workshops and a written technical scope
- 02Architecture, data model and API design
- 03Full build with automated tests and CI
- 04Integration with your ERP, CRM and payment providers
- 05Documentation and handover training for your team
- TypeScript
- Node.js
- PostgreSQL
- React
- Go
Typical timeline
8–16 weeks to first release
02
Web and mobile apps
We build the three journeys that carry most of your traffic first, put them in front of real users, and expand from there. Bilingual by default — RTL is designed in, not retrofitted.
What's included
- 01Product design from wireframe to production UI
- 02One codebase for iOS and Android where it makes sense
- 03Arabic and English with full right-to-left support
- 04App Store and Play Store submission
- 05Analytics and crash reporting from day one
- React
- React Native
- Next.js
- Expo
- Figma
Typical timeline
4–12 weeks depending on estate size
03
Cloud infrastructure
We take estates that grew by accident and make them boring: one way to deploy, one place to look when something breaks, and a bill you can explain line by line.
What's included
- 01Infrastructure as code, reproducible from an empty account
- 02Migration plan with rollback at every step
- 03UAE and Saudi data residency configuration
- 04Monitoring, alerting and on-call runbooks
- 05A cost review that usually pays for the engagement
- AWS
- Azure
- Terraform
- Kubernetes
- Grafana
Typical timeline
6 weeks to a working pilot
04
AI automation
We only take AI work where the saving can be counted. Every engagement starts with a six-week pilot on your own data, and we tell you plainly if the numbers do not justify going further.
What's included
- 01A pilot on your real documents before any commitment
- 02Retrieval and extraction pipelines with human review
- 03Accuracy measured against a labelled test set
- 04Integration into the tools your team already uses
- 05Monthly reporting on time and cost saved
- Python
- TypeScript
- OpenAI
- pgvector
- LangGraph
Not sure which of these you need?
Most projects cross two or three of them. Describe the problem and we'll tell you what it actually takes.