AI that removes work, not AI for the sake of it.
Most companies don't need an AI strategy. They need three or four specific tasks to stop eating their team's week. We build those, into the software you already use.
Where we are with AI.
We're an engineering company adding AI to business systems, not an AI research lab. We build with the major model providers rather than training our own, we tell you when a problem doesn't need AI, and we don't publish claims we can't show you.
What we build.
AI assistants and agents
Answer questions and complete tasks using your company's own documents, records and systems, with permissions respected.
Document and data automation
Read invoices, forms, reports and records, pull out what matters, and move it into your systems.
Arabic and bilingual AI
Assistants and document processing that work properly in Arabic as well as English, including mixed documents.
AI engineers for your team
Add AI and data engineers to your existing team through our dedicated teams service.
The tasks worth automating first.
- A support team answering the same questions from documents that already exist.
- Staff retyping data from invoices, forms or PDFs into another system.
- Reports that take a day to assemble from several systems.
- Searching years of records for one clause, case or transaction.
If a task is rare, or the cost of a wrong answer is high, we'll tell you it isn't a good first candidate.
How an AI project starts.
- 1
Pick one task
We look at where time actually goes, and choose one task with a measurable before and after.
- 2
Prove it small
A working prototype on your real data, so you can judge quality yourself before committing.
- 3
Build it properly
Access control, audit logs, human review where it matters, and a fallback when the model is unsure.
- 4
Measure it
Time saved, error rates and usage, reviewed after launch.
Things we'll talk you out of.
- Putting a chatbot on your website because competitors have one.
- Letting AI make decisions about people, money or health without a human reviewing them.
- Sending your sensitive data to a model provider without agreeing where it goes and what's retained.
- Replacing a working process that nobody complains about.
Questions.
Where does our data go?
We agree that before building. Options include model providers with no-training guarantees, or models running in your own cloud when the data is sensitive.
Which models do you use?
Whichever fits the task, budget and data rules. We're not tied to one provider.
Can it work in Arabic?
Yes. Arabic and mixed Arabic-English documents need extra testing, and we plan for it rather than assuming it works.
How accurate is it?
That depends on the task. We measure it on your data during the prototype, and design human review into anything where a wrong answer is costly.
Can you add AI to software we already have?
Usually yes, if it has an API or a database we can work with.