AI systems that ship in production
A job description rarely describes the real risk in a product. It helps to work with someone who has already built something similar.
Discovery stays short and specific: users, data, and risks. After that we build the critical path first and strengthen it from there.
We work best with startups and product teams hiring AI engineering talent who want a partner that ships. Agents, MCP servers, RAG pipelines, and LLM features wired into real software rather than demos.
What you get
- Production AI agents with tool calling
- MCP servers connected to your stack
- RAG over company knowledge
- OpenAI and Claude product integrations
- One studio accountable for the result
- Design and engineering on the same schedule
- Support available after launch
How engagement works
As your AI engineer, we run a shared backlog, design reviews, and engineering sprints, and you keep one point of contact throughout.
- 01
Discover
Goals, constraints, data sources, and success metrics, all settled before we touch architecture or prompts. Nothing here waits on a handover between separate teams.
- 02
Design
System design, AI/tool boundaries, interface direction, and interaction prototypes. On AI engineering projects we favour practical architecture over trendy defaults.
- 03
Build
Modern stack, clean architecture, evaluated AI behavior, and iterative demos you can react to. The work for teams in Dubai stays tied to the outcome you asked for.
- 04
Launch
Ship, monitor, harden, and keep improving models, tools, and product after go-live. You see progress on the critical path every week.
How we build it, and why
The stack is chosen per project, not applied from a template. For AI engineer work these are the defaults, and the reason each one is on the list.
- OpenAI
- a second model provider, so a single vendor's outage or price change is not your problem
- Claude
- long-context reasoning and reliable tool calling for agent work
- MCP
- the Model Context Protocol, so your tools plug into Claude, Cursor, and other agent clients without a custom adapter for each
- LangChain
- orchestration for multi-step chains when the flow is genuinely complex
- Next.js
- server rendering and static generation in one framework, so marketing pages stay fast and app routes stay dynamic
- NestJS
- structure and dependency injection on the backend, which keeps a growing API from turning into a pile of route handlers
What the first weeks look like
- Days 1-3
Context and constraints
Codebase, deploy path, and what "done" means for the AI engineering. Short, because the useful version of this is specific.
- Week 1
First shipped slice
Something real goes out in the first week — production ai agents with tool calling rather than a setup ticket.
- Weeks 2-6
Build to the milestone
Pull requests, reviews, and weekly demos. You see the work as it happens rather than at a handover meeting.
- Handover
Documented and transferable
Runbooks, architecture notes, and a walkthrough, so the work does not depend on us still being here.
Weighing up your options
There are three realistic ways to get this built. Each is the right answer for someone.
A solo freelancer
Cheapest per hour and fine for a contained task. The risk on AI engineering is breadth — one person covering design, backend, infrastructure, and launch usually means one of them is weak, and there is no cover when they are unavailable.
A local agency in Dubai
Same timezone and a face to meet, which genuinely matters for some teams. You are also paying Dubai brands investing in premium digital products and AI. rates for the whole team including the layers that never touch your AI engineering, and a local shortlist is a small shortlist.
Arcode
A small senior team. The people who scope the AI engineering write the code, you get weekly demos instead of status decks, and the engagement ends when the thing is live and handed over.
Work we have shipped
Brain CMS
Frontend · Firebase · Analytics
Multi-module enterprise CMS with documents, calendars, video, and advanced analytics.
Content and operations system spanning enterprise modules with Firebase and rich media tooling.
- · Multi-module business domains
- · PDF and document management
- · Advanced charting suites
- · Calendar and media workflows
React · Redux Saga · Firebase · Chart.js · Video.js
CRM Dashboard
Frontend · Analytics
Customer relationship dashboard with management workflows and data visualization on Next.js.
Freelance CRM surface for managing relationships and visualizing key metrics, deployed on Vercel.
- · CRM management views
- · Data visualization
- · Responsive dashboard layout
- · Vercel deployment
Next.js · React · Tailwind · Vercel
Case Management Hub
Full-stack engineer · NestJS · Next.js
HIPAA-compliant healthcare SaaS for 150+ US organizations, with dual databases, realtime collaboration, billing, and secure client portals.
Enterprise case management platform for healthcare and social-work organizations with encryption, realtime messaging, Stripe billing, Zoom, and calendar sync.
- · HIPAA-ready architecture with encryption and audit logging
- · Realtime collaboration via Socket.io + Redis
- · Client portal and role-based access control
- · Stripe billing and document workflows
Next.js · NestJS · TypeScript · MongoDB · Redis · Socket.io
Working with teams in Dubai
Dubai brands investing in premium digital products and AI. We work with clients in Dubai remotely and keep overlapping hours in GST. We usually collaborate in English/Arabic.
How we work with Dubai teams
Dubai runs on GST, one hour ahead of us, so the overlap is effectively complete. We work the Sunday-to-Thursday week where clients do, and same-day responses are the norm rather than the exception.
What Dubai clients usually need
Dubai clients typically want a product that looks premium and holds up under real traffic: booking and marketplace platforms, branded commerce, and AI automation inside operations that are already running.
Contracts, data, and compliance
We invoice in AED or USD. Where products serve both English and Arabic audiences, right-to-left layout, Arabic typography, and localised content are planned into the design system instead of retrofitted.
