Sovereign GPU compute, built where your data lives.
CoreWeave, Lambda, and AWS solve a real problem — they just don’t solve it inside MENA. HyperAI is the GPU cloud for organisations whose data, by regulation or by choice, has to stay in country.
Three things sovereign AI buyers care about
If your training data, inference logs, or fine-tuning corpus contains anything covered by SAMA, NCA, PDPL, or sectoral residency rules — these are the questions you’ve already had to answer for your CISO.
Country-level residency
Workloads run in your country, contractually. No “region” with a quiet failover into a foreign jurisdiction. Audit trail in regional language.
Customer-controlled LLMs
Run open-weight models entirely on infrastructure you control. No inference data shipped to a third-party model provider. No multi-tenant model boundary to argue with the regulator about.
Compliance, by design
Designed for SAMA, NCA, and PDPL. The compliance brief is delivered with the cluster — your legal and risk teams aren’t reverse-engineering it from generic terms of service.
HyperAI vs CoreWeave / Lambda / AWS GPU
Where the global GPU clouds beat us on raw scale, we don’t pretend otherwise. Where they fall short on residency, sovereignty, and compliance — that’s where this comparison gets interesting.
| Capability | HyperAI | CoreWeave | Lambda | AWS p5/p4 |
|---|---|---|---|---|
| GPU types | H100, A100, H200 (request) | H100, H200, B200 | H100, A100 | H100, A100 |
| MENA hosting | Yes | No | No | No |
| Data residency | Country-level, contractual | Region-level | Region-level | Region-level |
| Sovereign LLM deployment | Customer-controlled | Multi-tenant | Multi-tenant | Provider-managed |
| SAMA / NCA / PDPL | Designed for | Out of scope | Out of scope | Out of scope |
| Local language support | Arabic, English, French | English | English | English |
| Inference latency to MENA | Sub-50ms | 200ms+ (cross-Atlantic) | 200ms+ | Region-dependent |
Your inference data should never leave the country it was created in. Especially not for AI.
HyperAI runs open-weight LLMs on customer-controlled GPU clusters in MENA — fine-tuning corpora, inference logs, and prompt history stay inside the regulated perimeter. The compliance documentation is part of the deployment, not an afterthought.
bytes leave your jurisdiction
Where each platform wins
For unregulated, scale-first workloads with no residency story to defend, the global GPU clouds are the right call. For everything else inside MENA, sovereignty changes the math.
Sovereignty changes the math
- Any workload subject to SAMA, NCA, PDPL, or sectoral data-residency rules
- Sovereign AI deployment — open-weight LLMs running where customer data is the training/inference signal
- Latency-sensitive inference for MENA users (sub-50ms regional response)
- Audit trail and compliance documentation needed in Arabic, English, or French
Scale and unit economics dominate
- Pure unit economics for unregulated workloads — non-regional infrastructure can be cheaper
- Massive scale (1000+ GPU clusters) — hyperscalers and CoreWeave have more inventory
- Bleeding-edge GPU access (B200, GB200) typically lands US-first by 6–12 months
- Tight integration with existing US-region ML pipelines and ecosystem tooling
What sovereign AI buyers ask first
Every CIO and CISO conversation we run starts with these four. If yours starts with a fifth, the consultation slot below is the right next step.
Can I migrate from CoreWeave or Lambda to HyperAI?
Can I run hybrid — sovereign in MENA, scale-out elsewhere?
What is “sovereign LLM deployment”?
Do you support fine-tuning on customer data?
What models can I run?
Run your AI inside your borders.
The 14-day POC is free, includes architecture, model selection, and inference benchmarks against your data. The output is a deployable cluster spec your CISO can sign off on.
