We build AI that does work inside the systems you already run, rather than software you have to visit. Here is how a project is scoped, what it involves, and what we will tell you before you commit.
Most of what gets sold as AI automation in Dubai is a chat window bolted to a website. The work that changes an operation looks different: an agent that reads an enquiry, checks it against your CRM, answers in the customer's language, books the appointment, writes the record back, and escalates to a person at a defined point.
That means the hard part is rarely the model. It is the integration, the permissions, and deciding precisely where a human takes over. Our enterprise AI automation guide sets out the sequencing in detail.
We start from one workflow that is already costing you measurable time, not from a platform. The first conversation is about where work currently queues, who it queues behind, and what happens when something goes wrong.
There is no useful market rate for this work, because the same brief means very different things depending on the state of your systems. Any firm quoting before seeing your data is quoting for a different project.
Some engagements should not start as automation at all. Where the underlying data is inconsistent enough, consolidation comes first, and we would rather say so than automate a process that will produce confident wrong answers faster than the manual version did.
We also put ownership in writing at the start: the integration code, the prompt and workflow logic, your data and anything derived from it, and the environment it runs in. The practical test is simple — if this relationship ended in six months, what could you take elsewhere, and what would have to be rebuilt? If you are evaluating several firms, the five questions that separate providers is the buyer's-side version of this page.
Deployments sit inside your own cloud environment where the requirement calls for it, including on AWS services such as Bedrock. That gives private inference within your network boundary and audit logs, but it does not make a deployment compliant on its own — that is a property of how it is configured, and it stays your responsibility. The regulatory picture in the UAE is genuinely layered, and AI governance and data privacy in the UAE covers what needs deciding at architecture time rather than at launch.
We are based in Dubai and most of our work is with UAE and wider GCC operations — real estate, professional services, retail and B2B sales teams. That matters mainly because the channel mix here is different: WhatsApp carries conversations that elsewhere would sit in email, and enquiries arrive in several languages a day.
The services page lists the eight layers we build across. If you would rather start from a specific problem, tell us which systems you run and we will show the layer working against one of your own workflows.