AI and automation
AI inside your operations, not on top of them
Your company does not need a smarter model. It needs one wired to your data, your permissions and the way you actually work. An agent that does not know your stock levels or your returns policy gives a beautiful, wrong answer.
The shift
This stopped being an experiment and became a budget line
Three figures explaining why companies here started moving.
$320B
Projected contribution of AI to the Middle East economy by 2030
PwC · The potential impact of AI in the Middle East
11%
That contribution as a share of regional gross domestic product
PwC · same estimate
12.4%
Saudi Arabia's share of its own GDP, the highest after the UAE
PwC · country breakdown
What we build
Five agents, each solving a defined problem
Start with one, add the rest once it proves out.
Customer support agent
Answers on WhatsApp and the site from your own documents, and hands to a person the moment a question exceeds its limits.
Lead qualification agent
Replies to a new lead within a minute, asks the qualifying questions, and passes it to the rep already ranked by priority.
Process automation
Connects the repeated steps between your systems: an approval, a notification, an entry, a report, with no copying in between.
Document processing
Reads an Arabic invoice or contract and returns structured fields that go straight into your system.
Internal knowledge assistant
Answers your staff from company policy and files, with the source named and each department seeing only its own.
Governance and review
A log of every answer and the source behind it, plus written limits on what the agent is permitted to say and to do.
Standards
What goes into every AI project we build
Without exception, however small the scope.
Accuracy and limits
- Answers drawn from your sources, not general knowledge
- The document behind every answer, named
- A clear refusal when no reliable answer exists
- A handover to a person at the edge of its remit
- A list of subjects the agent will not discuss
Operation and governance
- A full conversation log open to review
- Permissions setting what each user can see
- Testing against real questions before launch
- A monthly measure of how often it is right
- An instant off switch in your team’s hands
Selection
We start with the case that returns a measurable result
Not every repeated task is a candidate. We choose the first against clear criteria: high frequency, stable rules, available data, and an effect measurable within a month.
How we select the first case
Questions
What gets settled before an AI project
Does our data leave the company?
What if the agent answers incorrectly?
How long to a first launch?
Does it replace our staff?
Start here
Tell us about your project
Send us two lines about what you need on WhatsApp. We reply, book a short scoping call, then send a written plan with cost and timeline before you commit to anything.