Sovereign AI Platform
Arabic Language Models Built for Sovereignty
Two specialized models. Seven benchmark validations. Complete data control. Deploy on-premises without vendor lock-in or unpredictable costs.
Sovereign AI Architecture
Complete control from data ingestion to inference
On-Premises Deployment
Data never leaves your infrastructure. Full GCC compliance.
Hybrid Architecture
Route intelligently for cost reduction.
Fine-Tuning
Build custom models for your specific domain securely.
Sovereign AI Architecture
Complete control from data ingestion to inference
On-Premises Deployment
Data never leaves your infrastructure. Full GCC compliance.
Hybrid Architecture
Route intelligently for cost reduction.
Fine-Tuning
Build custom models for your specific domain securely.
Key Features
Built for Enterprise Arabic AI Applications
Dual-Model Architecture
Optimize costs by intelligently routing traffic based on complexity.
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LLM-X [Flagship]
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LLM-S [Efficient]
Trained FOR Arabic
Not just trained ON Arabic. Deep understanding of cultural context.
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MSA + Major Dialects (GCC, Levantine, Egyptian)
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Deep morphological understanding
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Seamless Code-switching (Arabic/English)
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15-40% better performance on dialects
Data Sovereignty
Your data never leaves your infrastructure. No foreign APIs.
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GCC Compliance
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Air-gapped Networks
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Attorney-client Privilege
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Proprietary Security
Cost Predictability
Flat licensing vs unpredictable per-token API costs.
100B Tokens/month Example:Cloud API: Expensive, unpredictable
Arabic.AI: Predictable License
Stanford Helm Arabic Benchmarks
LLM-X vs Top 5 Models - Overall Performance
verage across 7 Arabic benchmarks (29 models evaluated)
Overall Average Performance (7 Benchmarks)
🥇 LLM-X
86.3%
Source: Stanford CRFM HELM Arabic Leaderboard (December 2025) Independent third-party evaluation
Real-World Applications
Proven results across government, finance, and legal sectors
Cloud APIs struggled with Gulf Arabic (68% accuracy). Data sovereignty blocked cloud
deployment.
Solution:
LLM-S for intent classification, LLM-X for policy questions. On-prem deployment.
Results:
• ✅ 94% accuracy on dialect
• ✅ Data sovereignty achieved
Real-time fraud detection required <100ms. External APIs were too slow (200ms+).
Solution:
LLM-S on edge nodes. Fine-tuned on 5 years of proprietary fraud data.
Results:
• ✅ 87ms avg inference time
• ✅ 91% detection accuracy
Global LLMs missed dialectal legal terms (72% acc). Privilege blocked foreign APIs.
Solution:
LLM-X for deep analysis, fine-tuned on historical contracts. Air-gapped deployment.
Results:
• ✅ 94% legal term accuracy
• ✅ 60% manual time reduction
Deployment Comparison
Why organizations choose Arabic.AI over cloud APIs
| Feature | Agentic Studio | Cloud AI Tools | Open Source |
|---|---|---|---|
| Data Sovereignty | Complete | Limited | Manual setup |
| Arabic Optimization | Native | Basic | None |
| Unlimited Workflow Calls | Yes | No | Yes |
| Self-Hosted Deployment | Yes | Cloud only | Yes |
| Custom LLM Support | Full | Limited | Yes |
| Flat Annual Pricing | Yes | Per-call | Free |
Data Sovereignty
Arabic Optimization
Unlimited Workflow Calls
Self-Hosted Deployment
Custom LLM Support
Flat Annual Pricing
Ready to Deploy Sovereign AI?
Schedule a technical consultation to discuss deployment architecture, ROI analysis, and industry-specific use cases.
