SM Stratagem builds generative ai development for Dubai teams that care about deployment, evaluation, and monitoring — not just the demo that impresses the boardroom.
We build generative ai development for teams in Dubai that need working software, not a slide deck for next quarter's steering committee. Dubai's pull for us is free-zone tech and trade, and teams sitting inside DIFC, DMCC, and the tech free zones rarely want another pilot that dies before rollout. In practice this looks like generative AI features that ship inside your product, not standalone demos — the code we ship is boring by design and easy for the next engineer to read. The engineering is only half of it — we also leave you with the evals, the dashboards, and a rollback plan for the day something goes sideways. We deliver across United Arab Emirates and the GCC in English and Arabic, with a project lead who owns delivery end-to-end rather than a chain of handoffs. Our differentiator for generative ai development in Dubai is honest scoping — if the smallest useful version fits in a month, we say so and we build that first. If the project has already stalled once, the shape of the first release was usually wrong — that's fixable in a week, not a quarter.
Buyers in Dubai are done with pilots. What they want now is one production system, measured, running, and reducing a real cost line or lifting a real revenue line. That's the frame we work inside.
GenAI features that live inside your existing product surface, using your auth, your billing, your data, and your design system — not a separate app users have to discover.
Every GenAI feature has a cost-per-request and a p95 latency budget from day one. When usage scales, the finance conversation doesn't become a fire drill.
Users don't wait ten seconds staring at a blank screen. We stream, we degrade gracefully when the model provider is slow, and we cache what's safe to cache.
GenAI that draws from your own content, your own tone of voice, and your own product constraints, not a generic assistant that could just as easily be a competitor's.
Drafting, rewriting, and summarising inside your product, respecting your data, your tone, and your permissions model.
Marketing copy, images, and structured briefs generated in-brand and reviewed by a human before publish.
Generated recommendations, explanations, or nudges tailored to the customer, with the reasoning surfaced so trust is earned.
For SaaS operators in DIFC, DMCC, and the tech free zones, we ship generative AI that plugs into the product you already sell, not a demo bolted on top. Auth, billing, and multi-tenant data separation are treated as day-one requirements, not backlog items.
A chatbot is one shape a generative AI system can take. Generative AI more broadly covers any feature where the output is created rather than looked up — drafting, summarising, generating images, personalising messages, translating tone. The engineering discipline is the same: ground on your data, budget cost and latency, evaluate quality, monitor in production.
Cost budgets per feature, cheaper models for cheaper work, caching where the output is safe to cache, and streaming so users don't pay for full completions they don't wait for. We instrument every call so you can see cost per feature per week and catch drift before it lands on a bill.
A well-scoped feature inside an existing product is usually two to four weeks to first release. That covers prototyping, integration with your auth and data, cost and latency instrumentation, and an initial eval set. Timelines stretch when the surrounding product is missing pieces — auth, billing, tenant isolation — that we then have to build first.
Both. Text is the majority of what we ship because it fits the most business use cases, but we build image generation (Stable Diffusion, DALL·E, Midjourney API) and increasingly short-form video generation for marketing and personalisation use cases. Same engineering discipline, different models.
Model choice matters here. We use providers whose terms allow commercial use of generated content, we track provenance in the metadata of anything we produce, and for high-stakes content (legal, medical, regulated marketing) we recommend human review before publish. If you have specific IP constraints we design the model choice around them.
Yes, and we recommend it. The pattern that works is ship one GenAI feature end-to-end — instrumented, budgeted, evaluated — and use it as the template for the next three. That's cheaper than trying to design a platform up front for features you haven't validated yet.
Yes — most of our client base sits in DIFC, DMCC, JAFZA, and Dubai Internet City. Vendor onboarding and procurement look different in each free zone, and we've been through them enough times to move faster than a firm doing it for the first time. Contracts, POs, and invoicing route through a UAE mainland entity we already run.
SM Stratagem builds enterprise ai solutions in Dubai, United Arab Emirates. AI that clears governance. Vendor-review ready. Multi-tenant and audit-friendly.
SM Stratagem builds machine learning development in Dubai, United Arab Emirates. ML that reaches production. Monitored for drift and quality.
SM Stratagem builds ai integration services in Dubai, United Arab Emirates. AI inside the systems you already run. CRM, ERP, help desk, product.
SM Stratagem builds generative ai development in Doha, Qatar. GenAI inside your product. Grounded on your data. Cost and latency measured. Book a scoping call.
SM Stratagem builds generative ai development in Kuwait City, Kuwait. GenAI inside your product. Grounded on your data. Cost and latency measured.
We'll scope the first release, define the eval set, and give you a build plan you can hand to any engineering team — ours or yours.