Why AI?
AI solutions here means systems that do work currently consuming your team's hours: classifying requests, extracting data from documents, answering repeated enquiries, forecasting demand. We build on existing models or tune models on your data, and we measure the effect before scaling it.
Where we start
From one painful, measurable process — not from the technology. We establish what it costs in time and money today, build a working prototype on your real data, and compare. If the number does not improve, we do not scale it. That is a commitment, not a caveat.
Where this actually works
An assistant that answers your customers in your language and tone and knows your catalogue; automation that reads invoices and documents into your system; classification and routing of inbound requests; analysis that forecasts demand or customer churn.
Your data
Customer data is processed under the Saudi Personal Data Protection Law, with you as the controller and us as processor on your behalf. Your data is not used to train third-party general models without a legal basis and explicit agreement.
What we do not promise
We do not promise that AI replaces your team, nor absolute accuracy. We promise a before-and-after measurement, and that we will tell you when the technology is not the answer.
- Start from one measurable process and compare the number before scaling
- Assistant that answers in Arabic in your business's register and knows your products
- Extraction from invoices and documents straight into your system
- Automatic classification and routing of inbound requests
- Models tuned on your data where it earns its cost, not by default
- Processed under the Personal Data Protection Law, with you as controller
Our AI Services
What makes our services stand out
Chatbots
Intelligent conversational AI
Predictive Analytics
Data-driven predictions
Computer Vision
Image and video analysis
NLP
Natural language processing
Technologies We Use
Powered by cutting-edge tech stack
How We Implement AI
How we turn your idea into reality
- 011
Data Collection
Gathering relevant data
- 022
Model Training
Training AI models
- 033
Testing
Validating accuracy
- 044
Deployment
Integrating with your systems
Pricing Plans
Choose the plan that fits your needs
Basic Plan
Perfect for small projects
- Basic design
- Technical support
- 1 month free maintenance
- Email support
- Basic SEO setup
- Mobile responsive
Professional Plan
For medium businesses
- Advanced design
- 24/7 support
- 3 months maintenance
- SEO optimization
- Performance monitoring
- Priority support
Enterprise Plan
For large corporations
- Custom design
- Dedicated support
- Annual maintenance
- Strategic consulting
- Advanced security
- SLA guarantee
FAQ
Answers to common questions
Where do I start with AI in my company?
Is my customer data used to train models?
How much does an AI project cost?
Will AI replace my staff?
Fine-tuning or retrieval-augmented generation?
Both come up in every AI project and are frequently confused. One teaches a model a manner; the other gives it knowledge.
| Criterion | Fine-tuning | Retrieval-augmented generation |
|---|---|---|
| What it improves | Style, format, dialect, a repeated task | Knowledge of your content and documents |
| Updating information | Requires retraining | Immediate — update the document |
| Citing a source | Not available | Available, and can point at the document |
| Initial cost | Higher: data preparation and training | Lower: indexing and search |
| Risk of invented answers | Remains | Lower, because answers are bounded by what was found |
| When it is not worth it | When better context in the prompt would do | When the problem is manner, not knowledge |
Our recommendation
Always start with retrieval-augmented generation — cheaper, faster, solves most cases, and allows a source to be cited. Fine-tuning earns its cost when a task repeats heavily and prompting cannot control its manner, not because it sounds more advanced.