AI and Data
AI that does real work.
We build AI systems that answer customers, read documents and forecast demand, using your own data and running in the region you choose. It is for organisations that want a working result they can measure, not a demo.
Sound familiar?
Problems we solve.
- Customers ask the same questions in Arabic and English, and your team answers them by hand.
- Staff spend hours reading, sorting and typing up invoices, forms and letters.
- Planning relies on last year’s numbers and a lot of instinct.
- You have been asked to “do something with AI” and need a first step that is safe and measurable.
- Two departments bring different figures to the same meeting.
- Monthly reports take a week of manual work in spreadsheets.
What you get
Clear outcomes, not just hours.
- Bilingual assistants grounded in your policies, catalogue and documents
- Document processing that extracts, checks and routes information with human review
- Forecasting and recommendation models built on your historic data
- Evaluation suites that measure accuracy and bias before and after launch
- Data pipelines from your core systems into one warehouse
- Clear data models with agreed definitions for key numbers
- Dashboards for leadership and operational teams
- Data quality checks and access controls
Use cases
Where AI already pays its way.
Banking
Customer service assistants, KYC document checks, fraud signals
Retail
Bilingual shopping assistants, demand forecasting, product content
Healthcare
Appointment triage, clinical note summaries for review, claims checks
Government
Document intelligence, citizen enquiry routing, translation support
Logistics
ETA prediction, customs paperwork extraction, exception alerts
Real Estate
Lead qualification, lease abstraction, maintenance request routing
AI project stages
From idea to a system you can rely on.
- 2 to 3 weeks
Explore
We pick one use case, check the data and agree what success looks like in numbers.
- 4 to 6 weeks
Pilot
A working version used by a small group, measured against the agreed target.
- 4 to 8 weeks
Harden
Security review, monitoring, human review flows and integration with your systems.
- Ongoing
Scale
Roll out to more users or use cases, with regular accuracy reports.
How a project runs
Four clear phases, from call to launch.
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2 to 4 weeks
Discover
We learn how your business works, agree the problem worth solving and write down how the system will work.
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3 to 6 weeks
Design
We design the experience and the architecture together, and test key screens with real users.
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8 to 24 weeks
Build
Senior engineers build in two week releases you can see and use, with testing and security checks on every change.
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Ongoing
Run
We launch carefully, watch closely and either hand over fully or keep running the system for you.
Technology
Tools we use often.
We choose technology for your team and constraints, not our preferences.
- Python
- PyTorch
- Azure OpenAI
- AWS Bedrock
- LangGraph
- pgvector
- Airflow
- MLflow
- dbt
- Snowflake
- BigQuery
- Databricks
- Power BI
- Metabase
Questions
Asked and answered.
Will the assistant make things up?
We ground answers in your own approved content, show sources, and set the system to say “I don’t know” and hand over to staff when it is unsure. We test for this before launch.
Does it work well in Arabic?
Yes. We test Arabic and English separately, including local dialect phrasing, and tune retrieval for both.
What is a sensible first project?
One narrow, high volume task with clear numbers, such as answering the top 50 customer questions or reading one type of document.
How do we measure return?
We agree two or three numbers during Explore, such as handling time or queries resolved, and report on them every month.
Which warehouse should we use?
It depends on your cloud, volumes and team. We recommend one in discovery with the reasoning written down.
How long until we see dashboards?
The first useful dashboard usually arrives within four to six weeks.