Information Technology
Getting data ready for AI: the unglamorous part that decides the result
Most AI projects that stall do not fail on the model. They fail on data that nobody owns, nobody has cleaned and nobody is allowed to use.
Data & Artificial Intelligence
Data engineering, analytics and applied AI that turn records the organisation already holds into decisions and automation.
Overview
Most AI projects that disappoint fail on the data, not the model. Before training anything we bring the relevant data into one governed platform, fix the quality problems and agree definitions, so that a figure such as monthly revenue means the same thing in every report.
On that foundation we build dashboards for management, forecasting and optimisation models for operations, and generative-AI assistants that answer questions from contracts, policies and manuals in Arabic and English. Sensitive data can stay on premises or in an in-country cloud, with open-weight models where a public AI service is not acceptable.
What the service covers
| Service | Scope | Technologies and methods |
|---|---|---|
| Data platforms | Modern data warehouses, lakehouses and pipelines with governance, quality and lineage. | Lakehouse, Data pipelines, Data governance |
| Business intelligence | Dashboards and self-service analytics that give leaders one version of the truth, in Arabic and English. | Dashboards, KPIs, Self-service BI |
| Machine learning | Forecasting, optimisation, anomaly detection and computer vision for operations, finance and logistics. | Forecasting, Computer vision, MLOps |
| Generative AI and agents | Arabic-capable assistants, document intelligence and AI agents running on your private data, on cloud or on premises. | LLM applications, RAG, AI agents |
| AI governance | Policies, model risk management and controls for responsible, explainable AI. | Model risk, Explainability, ISO/IEC 42001 |
How we work
Discover
We map the process, the users and the constraints before proposing any technology.
Design
Architecture, user experience, security model and delivery plan, agreed with your team.
Build
Short delivery cycles, with working software demonstrated every two weeks.
Launch
Testing, data migration, training and a controlled go-live.
Run and improve
Hand-over to your team, or 24/7 operation by ours under agreed service levels.
From our insights
-
-
Information Technology
Arabic-first design is more than flipping the layout
Mirroring a screen from left to right takes a stylesheet. Building a product that Arabic speakers find natural takes decisions about numbers, names, search and type that start on day one.
-
Information Technology
Cloud or in-country: deciding where regulated workloads should live
The question is rarely cloud versus no cloud. It is which data can go where, under which law, and what it costs to move it back if you change your mind.
Talk to us about Data & Artificial Intelligence
Send us the details and the practice lead will reply within one business day.