Two specialized language models. Four-layer architecture. Seven benchmark validations. Complete data control. Deploy on-premises or hybrid without vendor lock-in or unpredictable costs.
Four layers, each independently deployable. Your data enters at Layer 1 and never leaves your perimeter. Models live on your hardware. Agents call them through the platform. No foreign APIs in the loop.
Internal databases, documents, knowledge bases — structured and unstructured.
Proprietary knowledge curated for fine-tuning. Domain corpora, historical decisions, validated outputs.
Retrieval-augmented generation paired with continual fine-tuning. Secure data processing, role-scoped retrieval, and domain adaptation without exposing raw documents to the model weights.
SECURE DATA PROCESSINGFlagship model for complex reasoning, legal drafting, and policy work.
86.3% ACCURACY · FLAGSHIPEfficient model for high-volume classification, fraud detection, and edge deployment.
78.4% ACCURACY · EFFICIENTVisual workflow builder. Full API. On-premise tooling. 200+ connectors. Where the Suite, your custom agents, and your existing systems meet.
WORKFLOW · FULL API · ON-PREMISE TOOLSEvery layer of the stack — tokenization, training data, evaluation harness, inference pipeline — was rebuilt for Arabic. The 15–40% performance gap generic LLMs see on dialects and code-switching is engineered out by design.
Route traffic by complexity. LLM-X handles reasoning-heavy tasks. LLM-S handles volume at a fraction of the compute.
MSA plus every major dialect. Morphological awareness. Seamless code-switching. Diacritization. Root extraction. The stuff translation-bridged models quietly get wrong.
Data never leaves your infrastructure. No foreign APIs. Air-gapped deployment possible. GCC-compliant, attorney-client privileged, and audit-ready from day one.
Stanford CRFM's HELM Arabic leaderboard is the most rigorous public evaluation of Arabic language models. Seven benchmarks, twenty-nine models, independent scoring. Here's where LLM-X ranks.
Cloud AI is convenient until it isn't. When the regulator asks, the court subpoenas, or the jurisdiction changes, the cost of someone else holding your data gets real. Here's what that looks like compared to the alternative.
Your infrastructure, your control. Predictable licensing. Fine-tunable on your corpus. No token meters, no foreign cloud, no black-box exfiltration risk.
Fast to start, expensive to scale, and your most sensitive data is logged on servers you don't own in jurisdictions you can't control.
From fully managed private cloud to fully disconnected air-gap — pick the posture that matches your data and your regulator. Performance is consistent across all three.
Full platform hosted in an in-region private VPC. We run the infrastructure, you own the tenant. Best for teams that want a turnkey start.
Deploy into your AWS, Azure, Oracle, or private-cloud environment. Your perimeter, your keys, your audit logs. We provide the stack and the training.
Fully disconnected inference on your hardware. No outbound connections, no call-home, no cloud. For government, defense, and data that cannot leave the building.
We don't bolt compliance on. Each layer of the architecture ships with controls that match the regulatory posture of regulated industries across the GCC and EU.
No prompts, outputs, or embeddings leave your perimeter. Default, not opt-in.
At rest and in transit. Client-managed keys supported via KMS integration.
Every inference logged. Retrieval lineage preserved. SIEM-ready export.
Auto-redact personally identifiable information before it reaches the model, if required.
SAML, OIDC, Active Directory. Role-based access down to the document level.
UAE PDPL, KSA PDPL, Kuwait Data Protection, DIFC & ADGM privacy frameworks.
Zero outbound connections. Offline license validation. No call-home telemetry.
Legal-hold-ready, attorney-client privilege preserved, defensible audit trail.
Schedule a 30-minute technical consultation. We'll walk through deployment architecture, data flow, and an ROI analysis specific to your data sensitivity and scale.