nehlum
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Control Plane
GOVERN · AUDIT · ENFORCE
Private Data
Local Inference
Audit Logs
NO EXTERNAL CALLS
nehlum Services On-Premise & Self-Hosted AI
Capability Overview

On-Premise & Self-Hosted AI for Regulated Industries.

Intelligent systems that stay entirely within your walls — and entirely under your control. Sovereign-grade AI for organizations that cannot send their data anywhere.

Sovereign by architecture No external calls Audit-ready by design KSA-native
Book a discovery session See the framework
100%
Processing inside your boundary
0
External API dependencies
3
Validated deployment models
Air-gap
Capable lifecycle
01OUR POINT OF VIEW

AI adoption stalls exactly where the stakes are highest.

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.

02THE PROBLEM

Manual processes don’t scale — and standard AI is a liability.

Scale limitations

Manual review and analysis can’t keep pace without adding headcount.

Data residency risk

Sensitive content cannot leave sovereign environments, full stop.

Hidden external dependencies

Tools labelled “on-premises” can still depend on outside services.

Trust & traceability

Outputs must be explainable and defensible when an auditor asks.

03THE GAP

Neither public AI nor “standard on-prem” clears the bar.

Public AI Solutions

Processing happens on vendor infrastructure, outside the Kingdom
Sensitive content is exposed to external systems
Audit trails are incomplete or inaccessible

“On-Premises” Vendor Offerings

Many retain external calls for telemetry and analytics
Model updates may be pushed without your review
True air-gap capability is rarely validated or certified

The gap is structural, not just technical. Genuine sovereignty is an architectural decision made before deployment — not a contract clause applied after.

04DEFINITION

Your data. Your models. Your boundary. Always.

Sovereign AI means complete organizational control over data, model selection, inference, and updates — with no dependency on external services.

Residency enforced by architecture, not by promise.
From To
Data processed on someone else’s infrastructure Every process inside your environment
Vendor-controlled model updates Version-controlled models you approve
Black-box answers Explainable decisions with citations
Contractual residency promises Residency enforced by architecture
05THE nehlum MODEL

Five principles, engineered into every deployment.

01

Model-Agnostic Architecture

An abstraction layer to select, switch, and update models on performance, cost, and regulation — without rebuilding the platform.

02

Private Knowledge Grounding

The system reasons against your repositories and standards, not general training data.

03

Controlled Inference

All processing stays within defined security boundaries. No external API calls, no vendor telemetry, no internet required for core operations.

04

Offline-Capable Lifecycle

Evaluate, update, fine-tune, and deploy entirely without internet — built for air-gapped environments.

05

Human-in-the-Loop Governance

High-risk, ambiguous, or low-confidence outputs route to qualified reviewers. AI augments judgment; it doesn’t replace it.

06GOVERNANCE LAYER

The Private AI Control Plane.

What turns AI tools into a governed, enterprise-grade platform.

Model-Agnostic Orchestration

Switch models and inference engines without touching the application layer.

Prompt Policy Enforcement

Validate inputs against policy before inference; block violations at the gateway.

Role-Based Access Control

Govern who can submit, review, modify, and access governance functions.

Full Logging & Observability

Capture every request, decision, output, and latency for audit and optimization.

Human-in-the-Loop Escalation

Route low-confidence or ambiguous cases to qualified human reviewers.

Compliance Reporting

Generate structured audit reports with evidence, reasoning, and reviewer actions.

07TECHNICAL OVERVIEW

Deterministic certainty plus probabilistic intelligence.

Deterministic Components

Rule-based checks confirm mandatory elements, required clauses, and structure. Binary signals with absolute certainty.

Clause presence Formatting References Approval workflows

Probabilistic AI Reasoning

Language-model analysis evaluates semantic meaning, flags ambiguity, contextual conflicts, and risk that rules miss.

Confidence scores Evidence citations Review priorities
Together, they produce results that are comprehensive and defensible.
08DEPLOYMENT

Pick your level of isolation. We’ve validated all three.

A

Fully On-Premises / Air-Gapped

Maximum isolation, zero internet. Local inference on internal GPUs, on-prem vector database.

Best for: Highly sensitive or air-gap-mandated environments.
B

KSA-Only Cloud

Cloud infrastructure in Saudi regions only, private VPC, customer-managed keys, no cross-region replication.

Best for: Cloud flexibility with data residency in KSA.
C

Hybrid Control Plane

Governance and sensitive data stay on-prem; inference flexes for performance and cost under central control.

Best for: Scale without compromising sovereignty.
09AI APPROACH

Two approaches, matched to your maturity and accuracy needs.

OPTION 1 · RAG Recommended start

Retrieval-Augmented Generation

Model grounded in your internal repository via a vector database; updates by refreshing source content.

Regulatory updates reflected fast — no retraining
Strong auditability through cited sources
Lower operational risk
OPTION 2 · FINE-TUNE Only if RAG proves insufficient

Fine-Tuned Model (LoRA / QLoRA)

Model parameters adapted with domain-specific training data.

Better on specialized vocabulary
Less reliance on retrieval quality
More consistent on repetitive tasks

Fine-tuning follows RAG only when evidence shows retrieval can’t meet validated accuracy requirements.

10MODEL MANAGEMENT

Every model change — tested, approved, documented, reversible.

01
Sandbox Evaluation
New versions tested in isolation against compliance benchmarks.
02
Domain Adaptation
Targeted LoRA / adapter updates refine behavior.
03
Test & Validate
Known scenarios confirm accuracy, consistency, and explainability.
04
Version & Deploy
Approved versions registered and promoted, with rollback support.

Model registry with full version history, metrics, and change rationale; audit logs for every approval and deployment.

11USE CASES

Built for the institutions that can’t compromise on control.

Government & Public Sector

Sovereign document, policy, and citizen-data systems.

Banking & Finance

SAMA-aligned analysis, risk, and compliance on data that never leaves.

Healthcare & Life Sciences

PDPL-compliant patient and research intelligence.

Energy, Defense & Critical Infra

Air-gapped AI for the highest-sensitivity environments.

Common workloads
Compliance & policy validation Private GenAI assistants RAG knowledge bases Governed agentic workflows
12ECOSYSTEM

Right-sized models. Sovereign infrastructure.

Larger models where infrastructure allows; small language models where footprint and isolation matter most.

Self-Hosted Models SLMs for easier on-prem deployment and lower cost
LLaMA 3 8B
Mistral 7B
Phi-3
DeepSeek-R1 8B
Platform Stack
On-prem GPU inference
Private vector database
Embedding & semantic search
Model registry & MLOps
KSA Cloud Regions Private VPC, CMEK, RBAC, full audit logging
Azure — Saudi Arabia North
Google Cloud — Saudi Arabia
13OUR COMMITMENT

Honest about capabilities. Rigorous about governance.

Compliance assistance, not legal certification

The platform validates and flags for review; final determinations stay with qualified professionals.

Verified data residency, not assumed

Residency is enforced through infrastructure design, not vendor marketing.

Honest risk framing

No technology eliminates compliance risk; we design for it, produce audit-ready outputs, and keep humans in the loop.

Precise terminology

“Designed for compliance,” “audit-ready,” “governed operations” — we describe what the architecture actually delivers.

Human oversight by design

High-stakes and novel scenarios escalate to qualified reviewers.

14WHY nehlum

Sovereignty by architecture — on proven foundations.

Complete Data Sovereignty

Every component, process, and data element stays within your boundary across the entire lifecycle.

Explainable & Auditable by Design

Transparent reasoning and traceable decisions; every output is defensible.

Built on Proven Foundations

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.

15NEXT STEPS

Let’s build AI you can keep inside your walls.

01

Discovery Session

Understand your data, obligations, and isolation requirements.

02

Sovereignty Assessment

Map workloads to the right deployment model (A / B / C).

03

Deployment Roadmap

Co-create a phased path to a governed, self-hosted AI platform.

01Company Profile

Everything nehlum, in one document.

Capabilities, product ecosystem, certifications, and global delivery — distilled into a single, share-ready PDF.

Capabilities Product ecosystem Certifications Global delivery AI Systems AI Services
Download Profile PDFA4Updated 2026
nehlum
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