Services
AI & Automation in Saudi Arabia
Applied AI uses language and vision models to automate work that was previously manual: answering repeat enquiries, extracting data from documents, routing requests, drafting first-pass content. The engineering that matters is rarely the model itself — it is retrieval quality, evaluation, and the guardrails that stop a confident wrong answer reaching a customer. Arabic adds a real constraint: dialect coverage and Arabic retrieval quality vary considerably between models, so we benchmark on your content before committing to one.
| Typical timeline | 4 weeks to a measured prototype; 10–16 weeks to production |
|---|---|
| Languages | Arabic and English, benchmarked separately |
| Evaluation | Held-out test set with reported accuracy, not vendor claims |
| Data handling | PDPL-aware: documented storage, retention and cross-border position |
01Outcomes
What actually changes
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01
A defined task automated end to end, with an accuracy measurement you can audit — not a chatbot bolted onto a homepage.
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02
Arabic performance benchmarked on your own documents rather than assumed from an English demo.
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03
Human escalation designed in, with a logged trail of what the system answered and why.
02What you get
Deliverables
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Use-case assessment with expected cost, accuracy and risk per candidate
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Retrieval pipeline over your own content, with evaluation harness
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Bilingual assistant or automation with escalation to a human
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Guardrails: refusal behaviour, source citation, logging and review queue
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PDPL-aware data handling: what is stored, where, and for how long
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Operator dashboard and retraining procedure
03Pricing
What it costs
Cost depends on scope and project requirements. Contact us for a quote tailored to your project.
A note on the number
Indicative bands, excluding 15% VAT. Final scope is quoted after a discovery call.
04How we work
How we deliver this
01
Use-case triage
Score candidate tasks on volume, error tolerance and measurability. Drop the ones that do not survive.
02
Baseline
Establish current cost, handling time and error rate, so improvement is provable.
03
Prototype & evaluate
Build against a held-out test set in Arabic and English; report accuracy honestly.
04
Harden
Guardrails, escalation, logging, PDPL review, cost controls.
05
Operate
Deploy, monitor drift, review the escalation queue, retrain on real failures.
05Technologies
What we build with
- OpenAI
- Anthropic Claude
- Azure OpenAI
- Vector databases
- Python
- LangChain
- Evaluation harnesses
06Questions we are asked
Questions clients ask
01Will it work properly in Arabic?
Sometimes, and the honest answer is that it varies by model and by dialect. Modern Standard Arabic is handled well by the leading models; Gulf dialect and mixed Arabic-English input are weaker, and retrieval over Arabic documents degrades if the source PDFs were scanned rather than born digital. We benchmark on your actual content and report the number before you commit budget.
02What does PDPL mean for an AI assistant?
If the assistant processes personal data of Saudi residents, the Personal Data Protection Law applies — including to processing that happens outside the Kingdom. That means a privacy notice covering the purpose, a lawful basis, honouring the five data-subject rights within thirty days, and a documented position on cross-border transfer. We design the data flow around that from the start rather than retrofitting it.
Related services
This work is usually commissioned alongside Software Development, AI Search Visibility (AEO/GEO), Search Engine Optimisation.