Intelligent systems that stay entirely within your walls — and entirely under your control. Sovereign-grade AI for organizations that cannot send their data anywhere.
Banks, ministries, hospitals, and operators of critical infrastructure have the most to gain from AI — and the least freedom to use the public kind. Their data can’t leave the Kingdom, can’t reach a vendor’s servers, and can’t appear in someone else’s training set. We build AI that lives inside their boundary, so the regulated can finally move as fast as the unregulated.
Manual review and analysis can’t keep pace without adding headcount.
Sensitive content cannot leave sovereign environments, full stop.
Tools labelled “on-premises” can still depend on outside services.
Outputs must be explainable and defensible when an auditor asks.
The gap is structural, not just technical. Genuine sovereignty is an architectural decision made before deployment — not a contract clause applied after.
Sovereign AI means complete organizational control over data, model selection, inference, and updates — with no dependency on external services.
An abstraction layer to select, switch, and update models on performance, cost, and regulation — without rebuilding the platform.
The system reasons against your repositories and standards, not general training data.
All processing stays within defined security boundaries. No external API calls, no vendor telemetry, no internet required for core operations.
Evaluate, update, fine-tune, and deploy entirely without internet — built for air-gapped environments.
High-risk, ambiguous, or low-confidence outputs route to qualified reviewers. AI augments judgment; it doesn’t replace it.
What turns AI tools into a governed, enterprise-grade platform.
Switch models and inference engines without touching the application layer.
Validate inputs against policy before inference; block violations at the gateway.
Govern who can submit, review, modify, and access governance functions.
Capture every request, decision, output, and latency for audit and optimization.
Route low-confidence or ambiguous cases to qualified human reviewers.
Generate structured audit reports with evidence, reasoning, and reviewer actions.
Rule-based checks confirm mandatory elements, required clauses, and structure. Binary signals with absolute certainty.
Language-model analysis evaluates semantic meaning, flags ambiguity, contextual conflicts, and risk that rules miss.
Maximum isolation, zero internet. Local inference on internal GPUs, on-prem vector database.
Cloud infrastructure in Saudi regions only, private VPC, customer-managed keys, no cross-region replication.
Governance and sensitive data stay on-prem; inference flexes for performance and cost under central control.
Model grounded in your internal repository via a vector database; updates by refreshing source content.
Model parameters adapted with domain-specific training data.
Fine-tuning follows RAG only when evidence shows retrieval can’t meet validated accuracy requirements.
Model registry with full version history, metrics, and change rationale; audit logs for every approval and deployment.
Sovereign document, policy, and citizen-data systems.
SAMA-aligned analysis, risk, and compliance on data that never leaves.
PDPL-compliant patient and research intelligence.
Air-gapped AI for the highest-sensitivity environments.
Larger models where infrastructure allows; small language models where footprint and isolation matter most.
The platform validates and flags for review; final determinations stay with qualified professionals.
Residency is enforced through infrastructure design, not vendor marketing.
No technology eliminates compliance risk; we design for it, produce audit-ready outputs, and keep humans in the loop.
“Designed for compliance,” “audit-ready,” “governed operations” — we describe what the architecture actually delivers.
High-stakes and novel scenarios escalate to qualified reviewers.
Every component, process, and data element stays within your boundary across the entire lifecycle.
Transparent reasoning and traceable decisions; every output is defensible.
Drawn from validated patterns — governed GenAI assistants and private AI control planes in sensitive environments. Mature approaches, not experiments.
NCA-, SAMA-, and PDPL-aware, and Vision 2030-aligned — engineered for the Kingdom and the wider GCC.
Understand your data, obligations, and isolation requirements.
Map workloads to the right deployment model (A / B / C).
Co-create a phased path to a governed, self-hosted AI platform.
Capabilities, product ecosystem, certifications, and global delivery — distilled into a single, share-ready PDF.