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AI Development

AI that survives contact with a real business

The gap between an impressive demo and a system people use daily is where most AI budgets disappear. The demo is easy. Messy documents, access control, Arabic retrieval quality and the moment the model is confidently wrong — that is the actual work.

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01

Feasibility

An honest assessment of whether your data can support the use case, before anyone writes code.

02

Arabic retrieval

Text normalisation, hybrid search and reranking — because Arabic retrieval fails differently to English.

03

Sovereign deployment

Open-weight models self-hosted in-Kingdom where data cannot leave your network.

04

Guardrails

Citations, confidence thresholds, human approval gates and full audit logging.

Retrieve for facts, fine-tune for behaviour

Fine-tuning a model to teach it your company's facts is the most common and most expensive mistake in enterprise AI. It produces a model that states outdated information fluently and without citation, which is worse than one that says it does not know.

Retrieval keeps knowledge current and auditable. Fine-tuning is for consistent output format, institutional tone, or specialised domain language — not for adding facts.

Arabic is genuinely harder

Arabic retrieval suffers from rich morphology, absent diacritics, dialect variation, and enterprise documents that exist only as scanned images. Systems that work in English return poor results in Arabic until normalisation, hybrid search and reranking are addressed deliberately.

Where data cannot leave your infrastructure, open-weight models such as Qwen, Llama and DeepSeek run on a modest GPU server inside the Kingdom. Inference never touches a third-party API.

Questions

Can AI run entirely inside Saudi Arabia?+

Yes. Open-weight models can be self-hosted on in-Kingdom infrastructure or your own hardware, so no data leaves your network.

Should we fine-tune on our documents?+

Usually not. Fine-tuned knowledge cannot be cited and goes stale immediately. Retrieval keeps facts current and auditable.

Why does AI perform worse in Arabic?+

Rich morphology produces many surface forms of one concept, diacritics are usually absent, dialect differs from written Arabic, and many documents are scanned images needing Arabic OCR.

How do you stop it giving wrong answers?+

Retrieval with citations, an evaluation harness tested on real user questions, confidence thresholds that trigger escalation, and human approval gates on consequential actions.

Let's scope it

A free 30-minute call, then a fixed written quote within 48 hours.

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