Services
15 services across five lines, each with defined deliverables and a clear duration. Every client starts with a short service, then a project, then a subscription.
Line 1 · Diagnostics and readiness for national indices
National indices & compliance
Readiness for five national indices (Qiyas digital transformation, the National Data Index «Nadhi», the National AI Index, Digital Experience Maturity, and Website and Digital Content Efficiency) using the Takamul method.
We cover five indices together rather than one: evidence prepared once serves every index that asks for it.
- G1Starting point
Takamul diagnostic
One assessment that shows where the entity stands across five national indices at once, and ranks the top ten actions by their cross-index impact.
4 weeks - G2
Cycle readiness programme
A unified evidence library built once and mapped to every index’s standard codes, with each piece reviewed before submission and a monthly readiness calendar through the cycle.
10–14 weeks - G3Starting point
NDMO maturity & PDPL gap assessment
Measures the entity against the National Data Management Office specifications and the Personal Data Protection Law, with a risk-ranked closure plan.
2–4 weeks - G4Starting point
Website efficiency uplift
Lifts the entity’s score in the Website and Digital Content Efficiency index: accessibility, speed, security, search visibility and content quality, with a content policy that keeps the gain after handover.
6–8 weeks
Line 2 · Consistent numbers with one definition and owner
Data governance & one number
We resolve conflicting numbers before they reach leadership: one definition, one owner and one semantic layer feeding every dashboard.
We focus on governance and the semantic layer, not on how the dashboard looks.
- D1
“One trusted number” KPI programme
Ends conflicting numbers before they reach leadership: an approved definition and owner for every figure, and one semantic layer feeding every dashboard.
3–5 months - D2
Data management office set-up
The structure, roles and policies a data office needs to actually function, with owner and steward appointments and a first maturity plan.
6–10 weeks
Line 3 · Data fit for real use cases
AI readiness
A fast assessment that shows why AI pilots stall, followed by fixing the data, quality and governance underneath.
67% of Saudi executives in the ServiceNow Enterprise AI Maturity Index 2026 name data accuracy and management as the biggest barrier to scaling AI.
- A1Starting point
AI data readiness assessment
Shows why the entity’s AI pilots stall: which data is usable, how good it is, and what each use case is missing.
4 weeks - A2
AI readiness implementation
Delivers what the assessment found: an open-source data catalogue, quality rules and monitoring, and a training-data catalogue with documented usage rights.
3–9 months - A3
AI governance
A framework that makes AI use accountable: a model register, risk classification, human oversight, and alignment with SDAIA’s AI ethics principles.
8–12 weeks
Line 4 · Health data quality and governance
Health data
Standards and reference data models applied to health data: NPHIES exchange quality, a unified data model, and governance of sensitive data.
We work inside the client environment and are building this line with specialist health informatics partners.
- H1Starting point
Health exchange data quality
Reduces claim rejections caused by data quality before submission through NPHIES, measures the impact by first-pass acceptance rate, and adds an ongoing monitoring dashboard.
6–8 weeks - H2
Reference health data model
A unified data model and dictionary mapped to HL7 FHIR, with clinical and operational indicators defined once across every facility.
3–6 months - H3
Sensitive health data governance
Classification of health data and the sharing and access policies that meet the Personal Data Protection Law.
8–12 weeks
Line 5 · Ongoing support after delivery
Managed services & subscriptions
Every project ends in ongoing follow-through: a data office as a service, index tracking, and a managed data team under an SLA.
A head of data costs SAR 30–45k a month; a subscription gives the entity that leadership and discipline for a fraction of the cost.
- M1
Index tracking subscription
Keeps the entity ready between cycles: a short quarterly assessment, a continuously updated evidence library, and a leadership dashboard.
Annual subscription - M2
Data office as a service
Fractional data leadership that gives the entity what a full-time head of data would: policies, maturity tracking, vendor oversight and a monthly leadership report.
Annual subscription - M3
Managed data team
A ready team of a data engineer, a BI analyst and a quality specialist, working under an SLA with monthly reporting.
12 months
How engagements usually run
An entity starts with a scoped diagnostic, then decides what it actually needs.
Start with a free scorecard
We prepare your entity's scorecard across five national indices from published data, free and with no commitment, showing the visible gap and the priorities to close it.