What SDAIA Publishes, and the Evidence We Help You Build Against It
We are not a SDAIA partner and do not claim to be. What we do is build the governance and documentation evidence an organisation needs to demonstrate alignment with SDAIA's published data and AI frameworks, and hand it to you in a form your own compliance function can defend.
- Alignment gap assessment
- 4-6 wksAlignment gap assessment
- Evidence pack build-out
- 8-12 wksEvidence pack build-out
- Organisation-wide rollout window
- 90 daysOrganisation-wide rollout window
- Default hosting posture
- In-countryDefault hosting posture
Before you cite SDAIA alignment in a proposal or audit
- 01
Alignment evidence is not the same as a partnership
Ask any vendor, including us, to show the document behind a partnership or endorsement claim. If there is none, the claim should not be in the proposal.
- 02
Published guidance changes, evidence needs a review date
An evidence pack built two years ago against guidance that has since been updated is not current evidence, it is a historical record.
- 03
A gap documented honestly is stronger than a gap hidden
A reviewer trusts an evidence pack that names its own limitations more than one that claims full compliance with no caveats.
In Saudi Arabia
Who typically asks for SDAIA-alignment evidence, and what they expect
Requests for alignment evidence come from more than one direction. This is who asks, and what they are usually shown.
Internal compliance or risk function
A documented position against SDAIA's published national data governance guidance.
A control mapping and gap list, reviewed on a defined cadence.
Government or regulated-sector procurement
Evidence that a proposed AI system's data practices align with national guidance before contract award.
A data classification and hosting statement attached to the procurement submission.
NDMO-aligned data governance review
A named data owner and classification record for every dataset an AI system touches.
A dataset-level classification map with an accountable owner.
External or internal audit
Ability to reproduce the control mapping and show it has been kept current.
A version-controlled evidence pack with a documented review history.
Data classification reviews
A documented classification of datasets against the categories set out in national data governance guidance.
AI system documentation
Model cards covering training scope, known limitations and review cadence, in the form an internal reviewer would expect to see.
Procurement due diligence
Evidence a government or regulated-sector buyer can attach to a procurement file when assessing an AI system.
Internal audit preparation
A control mapping that shows, dataset by dataset, how a stated governance obligation is actually met.
Cross-border data flow reviews
Documentation of where data moves, and why, when a system touches more than one jurisdiction.
Board-level risk reporting
A summary a board can review without wading through the underlying technical documentation.
Where alignment evidence gets asked for
What we actually mean by alignment evidence
We read what SDAIA has published, not what a sales deck claims
Our starting point is the publicly available National Data Governance Framework and related SDAIA guidance, not a summary written to sound reassuring.
We do not claim a partnership we do not hold
If a page or a proposal claims a SDAIA partnership, ask to see the documentation. We will tell you plainly when we have none to show, because that is the honest answer.
Evidence is written for your compliance function, not for a pitch
The output of this work is a document your own risk or compliance team can defend to an internal or external reviewer, not a marketing artefact.
In-country hosting by default
Data classified as sensitive under PDPL is architected to stay inside Saudi geography before any pipeline is built.
Gaps are named, not smoothed over
Where an organisation's current practice does not align with published guidance, the gap is documented as a gap, with a plan to close it, not reframed as a strength.
The evidence outlives the engagement
Documentation and control mappings are handed to your team so the next audit does not depend on us being in the room.
Claiming alignment, or evidencing it, the difference shows up in an audit
A claim of SDAIA alignment costs nothing to write in a proposal. An evidence pack that survives a reviewer's questions costs the work of actually building it.
| Dimension | Unverified alignment claim | Documented alignment evidence |
|---|---|---|
| What is on file | A sentence in a proposal | A control mapping with a named owner |
| What happens under review | The claim cannot be substantiated | The mapping is walked through, dataset by dataset |
| Partnership language | Implied or asserted without documentation | Stated plainly as evidence work, not a partnership |
| Currency over time | Written once, never revisited | Reviewed on a defined cadence against current guidance |
What the evidence pack is built against
- Publicly available SDAIA guidance on data governance and AI, read as published, not paraphrased
- PDPL data classification for every dataset in scope
- A documented gap list where current practice does not yet align, with an owner and a timeline
- In-country hosting evidence for data classified as sensitive
- Model documentation for any AI system contributing to a decision or reported figure
- A version-controlled evidence pack that survives a change in your compliance lead
Building a classification record before a procurement submission
A regulated-sector organisation needed to submit a data governance position as part of a procurement process for a new AI system, and the draft submission asserted broad compliance without a dataset-level record behind it.
- 01We listed every dataset the proposed system would touch and classified each one against the categories set out in national data governance guidance.
- 02We identified two datasets where the classification was unclear because ownership had never been formally assigned, and worked with the client to assign it.
- 03We rewrote the compliance section of the submission to reference the actual classification record rather than a general compliance statement.
- 04We handed over the classification record as a living document, with a review date set before the next procurement cycle.
The submission went in with a dataset-level classification record attached rather than an unsupported compliance sentence, and the client's own team now owns the review cadence.
Related reading on Saudi data governance and AI delivery
Frequently Asked Questions
Is Bilytica a SDAIA partner?
No, and we do not claim to be. We build governance and documentation evidence against SDAIA's published guidance. If you see a partnership or endorsement claim attached to our name, ask us for the documentation, we will tell you plainly if there is none.
What does an alignment evidence pack actually contain?
A dataset-level classification record, a control mapping against published national data governance guidance, and, where relevant, model documentation for any AI system in scope. It is written to be defended by your own compliance function, not to read as a marketing document.
Can this evidence replace a formal regulatory approval?
No. Where a formal approval, certification or registration is required by a specific regulator, that process sits with the regulator, not with us. Our work is the underlying evidence a compliance function needs to support that process.
What happens if our current practice does not align with published guidance?
We document the gap plainly, with an owner and a timeline to close it. A documented gap with a remediation plan is a stronger position under review than an unsupported claim of full compliance.
How long does an initial alignment assessment take?
A gap assessment against one system or dataset scope is scoped with you based on complexity. Talk to our team with the scope you need reviewed and we will confirm a timeline.
Bring us your current SDAIA-alignment position
In a working session, a Bilytica governance lead will review what your organisation can currently show against SDAIA's published guidance, name the gaps plainly, and hand back a scoped plan to close them, without overstating what either of us can claim.