Applied AI
Enterprise AI subjected to measurement and governance before reaching the user.
AI projects rarely fail due to mathematical models; they fail due to undefined authoritative records, fragmented permissions, or the lack of precise criteria for handling incorrect responses before going live.
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01
Your evaluation set Actual queries your staff ask, drawn from your operational documents and human-labelled for accuracy.
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02
One threshold, agreed upfront A single performance baseline, documented before development begins rather than after results arrive.
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03
Systematic measurement Every release is measured against that baseline. Nothing here is negotiable once the build starts.
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CLEARS
Approved for Launch With the score, date, and audit log permanently recorded.
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DOES NOT
Blocked from Production You receive a technical report detailing the exact reasons for the shortfall.
We begin by addressing actual points of failure: identifying the officially approved data, enforcing permission boundaries, and strictly defining system behavior for out-of-scope queries. All of this is resolved as a prerequisite before selecting a model.
The Arabic language and local business context are core design pillars, not subsequent translation layers. This guarantees high-fidelity comprehension of official documents, scanned correspondence, and specialized terminology.
Every system we launch must pass an agreed-upon statistical accuracy gate. If the model does not clear the target percentage on your specific dataset, it does not move to production, and you receive a transparent report detailing the shortfall without delay.
What this covers
Selecting High-ROI Use Cases
Filtering initiatives based on data readiness, operational impact, and governance/compliance overhead.
Retrieval-Augmented Generation (RAG)
Intelligent search and query engines over your official documents, strictly bound by existing user permissions with no loopholes.
Building and Labeling Evaluation Sets
Preparing test sets drawn directly from actual staff queries, human-labeled to measure accuracy reliably.
AI Security and Governance
Enforcing source citation, masking personal data, and maintaining audit logs compliant with SDAIA controls.
Tell us what you are trying to solve.
Share the operational challenge and the regulatory or technical constraints you are working within. A consultant replies within two working days, in Arabic or English.