Services · Artificial intelligence

AI that does real work inside your business.

Q: Will the AI make mistakes?

Yes, sometimes, so we design for it. Language models can be wrong or overconfident. We limit what each system can do, test it against an evaluation set before launch, log every answer and route uncertain cases to a person. Your team reviews samples regularly so problems surface early.

Q: Where does our data go?

Where you decide, and nowhere it does not need to. We can deploy inside your own Azure or AWS tenant and use enterprise model endpoints that do not train on your data. Data handling is designed around the UAE Personal Data Protection Law and your internal policies. We document every data flow before go live.

Q: Do we need clean data before starting?

No, but we will tell you honestly what your data can support. Many language model projects work with documents and records you already have. Machine learning projects need more history and consistency. The discovery step shows which ideas your data can support now and which need preparation first.

Q: Can you work with our existing software?

Yes, connecting to existing systems is most of the work. We integrate with ERPs, CRMs, document stores, ticketing tools and messaging channels through their APIs. Codeeo also builds custom software and works with Microsoft Dynamics 365 and Odoo, so the AI and the system it depends on can be handled by one team.

Q: Who looks after the system after launch?

We can, or we hand it to your team with full documentation. Many clients keep us on a monthly support plan for monitoring, prompt tuning and model updates. Others take it in house after a handover period. Either way you hold the code, accounts and runbooks.

Codeeo plans, builds and runs AI development services in Dubai for companies that want working systems, not slide decks. We start from a process you already run, put AI where it removes effort, and keep a person in the loop where judgement matters. Assistants read and answer in English and Arabic, and interfaces support right to left layouts.

One team covers the full path from first idea to a model running in production, so nothing gets lost between a strategy firm and a build shop.

Get in touch See our services

Built for: Founders, operations heads and IT leaders at UAE businesses who want AI tied to a named process and a named owner.
Typical timeline: A focused prototype usually takes a few weeks, and a production rollout follows in phases once the prototype has been tested on real work.
What you own: You own the code, prompts, evaluation sets, data pipelines and cloud accounts, with nothing locked inside a Codeeo platform.
Rated: 4.7 / 5 from 23 Google reviews

200+ companies servedFrom a first store to an ADX listed developer

What you get

Eight services, one accountable team.

Most projects use two or three of these together. A support agent, for example, needs integration, automation and monitoring as much as it needs a language model.

Explain your project

AI consulting
We review your processes, data and systems and pick the use cases worth building first. You get a written roadmap with owners, risks and the order of work.
You spend on the two or three ideas most likely to pay back, and park the rest with a reason.
AI agent development
We build agents that answer customers, qualify leads, book appointments and update your CRM over WhatsApp, web chat or email. Each agent works within set rules and hands over to a person when it is unsure.
Routine conversations get handled around the clock while your staff deal with the cases that need them.
Custom AI and LLM apps
We design and build applications on OpenAI GPT models, Anthropic Claude, Google Gemini or open models such as Llama and Mistral. Typical builds include document review tools, search over internal knowledge and drafting assistants.
Your team gets a tool shaped around its own work instead of a general chat window.
AI integration
We connect language models to the systems you already run, such as Microsoft Dynamics 365, Odoo, Salesforce, SharePoint and your own databases. Data moves through secured APIs with permissions checked on every call.
AI answers reflect your live records, and staff stop copying data between screens.
AI automation
We automate multi step workflows such as invoice intake, onboarding checks and report preparation using Python, n8n and Power Automate. Steps that need a decision are routed to a named reviewer.
Back office work moves faster with fewer handoffs and a clear record of who approved what.
Machine learning
We train models for forecasting, churn, pricing support, fraud flags and classification using scikit-learn, PyTorch and TensorFlow. Every model is tested against a held back dataset before it is trusted.
Decisions that relied on gut feel get a measured second opinion your analysts can question.
Computer vision
We build vision systems with OpenCV and YOLO for document capture, stock counts, safety checks and quality inspection. Models run in the cloud or on cameras and edge devices on site.
Visual checks that tie up staff become steady, logged and reviewable.
MLOps and governance
We set up deployment, monitoring and retraining with MLflow, Docker and Kubernetes, plus policies, access controls and audit logs. Models are watched for drift and failures are alerted to your team.
AI stays reliable after launch, and you can explain to auditors how it was built and checked.

Who this is for

Where you are with AI decides where we start.

Buyers come to us at three different points. The first step changes, the standard of the work does not.

You are exploring AI

You know competitors are using it and staff are already trying ChatGPT, but there is no plan. We run a short discovery, look at your data and processes, and give you a ranked list of use cases with a clear first project.

Start with AI consulting.

You have a use case ready

You know the process, the owner and roughly what good looks like. We move straight to a prototype on your real data, test it with the people who will use it, then build it properly.

Start with a scoped build.

You are scaling AI already in use

You have pilots, scripts or a vendor tool in place, and now need it secure, monitored and connected to core systems. We review what exists, fix the weak points and put it on a supported footing.

Start with a technical review.

How an AI project runs with us.

01DiscoverWe map the process, the data and the people involved, and agree what the system should and should not do.
02PrototypeWe build a working version on real examples and score it against an evaluation set your team helps write.
03BuildWe harden the prototype with integrations, access controls, logging, human review points and tests.
04RunWe deploy, monitor quality and cost, retrain or adjust prompts when results slip, and report back each month.

How we work together

Pick the engagement that fits the stage.

Fixed scope projects suit a defined build. A monthly team suits ongoing development and support. Both include documentation and handover.

Discovery and pilot

Teams deciding where AI should start

A short, fixed piece of work: the use cases ranked, the data checked, and one pilot built against real examples so you can judge it on evidence rather than a demo.

Use cases ranked by value and risk
Data and systems review
A working pilot on your own examples
A written plan for what comes next

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Build and launch

A use case that is ready to go live

A written scope and a fixed quote, then the build: integrations, guardrails, an evaluation set and a launch with your team trained to use it.

Written scope and acceptance tests
Integration with your systems
Evaluation set and human review steps
Launch, training and handover

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Run and improve

AI that is live and needs looking after

A monthly plan to watch quality, cost and usage, update prompts and models as vendors change them, and add the next use case when the first one earns it.

Quality and cost monitoring
Model and prompt updates
A monthly report on usage and results
The same team that built it

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Technology

What we build this with.

Models are chosen per use case for quality, cost and where your data is allowed to go. The systems around them run on the stack below.

01Web

React
Next.js
TypeScript
Node.js
Laravel
WordPress

02Data and cloud

PostgreSQL
MySQL
MongoDB
AWS
Azure
Docker

Questions buyers ask about AI projects.

Which AI models do you use?

The one that fits the task, your data rules and your cloud.

We work with OpenAI GPT models, Anthropic Claude, Google Gemini, Azure OpenAI, AWS Bedrock and open models such as Llama and Mistral. We often test two or three on your own examples before choosing. You can switch models later because we keep prompts and evaluation sets separate from the model.

Will the AI make mistakes?

Where does our data go?

Do we need clean data before starting?

Can you work with our existing software?

Who looks after the system after launch?

Services that usually go with this one.

AI consulting and strategyKnow which AI projects to fund before you fund them.AI agent developmentAgents that do real work, with a person signing off.Custom software and business systemsThe system that replaces the spreadsheet nobody dares change.

Tell us what the business needs. We will tell you what to build first.

Schedule a free consultation and get a written recommendation, with costs, before you commit to anything.

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PROVEN RESULTS

4.7 / 5from 23 Google reviews