On-Premise LLM Deployment

Your own AI assistant running on your server. We install, configure, and maintain open-source language models on your infrastructure. Data physically never leaves your office.

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Language model loaded (70B parameters)
Network isolated — no external connections
System operational — accepting requests
System Status
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What's included

Infrastructure Audit

We assess your existing servers, network topology, and security requirements. Determine the optimal hardware configuration for your workload and user count.

Model Selection

Choose the right model for your use case: code generation, legal document analysis, Arabic language support, or general-purpose assistant. We benchmark and recommend.

Server Installation

Install and configure the inference engine on your server. Optimize for your GPU (NVIDIA, Apple Silicon) or CPU-only deployment. Full inference stack setup.

Web Interface

Deploy a browser-based chat interface so your employees can use AI through a familiar chat. No technical knowledge required.

System Integration

Connect to your Active Directory / SSO for authentication. API endpoints for internal systems. Audit logging for compliance. Webhook notifications.

Staff Training

Train your team on effective AI usage: prompt engineering, limitations, security best practices. Admin training for model management and monitoring.

How it works

From initial consultation to a running system in 1-2 weeks.

1

Discovery Call

We understand your requirements: number of users, use cases (legal, coding, documents, Arabic), security constraints, and existing infrastructure.

2

Infrastructure Assessment

On-site or remote audit of your servers. We check GPU availability, RAM, storage, and network configuration. If hardware is needed, we recommend specific options.

3

Deployment & Configuration

Install the inference engine, download and configure models, set up the web interface, integrate with your authentication system, and configure monitoring.

4

Testing & Training

Thorough testing with your actual use cases. Staff training sessions. Documentation handover. System goes live with monitoring in place.

Supported Models

We deploy the latest open-source models, selected for your specific use case and hardware.

Llama 3.3Qwen 2.5DeepSeek V3Falcon 3MistralGemma 2Command R+Phi-4JaisALLaM

Who needs on-premise LLM

Banks & Financial Institutions

Internal security policies prohibit any cloud AI, even sovereign. Deploy an air-gapped LLM for internal document analysis, compliance queries, and code assistance without data exposure.

Government & Public Sector

UAE and KSA government data often cannot leave the physical premises. On-premise LLM enables AI-powered workflows for classified communications, policy drafting, and citizen services.

Defense & Law Enforcement

Classified environments with no internet access. We deploy models on fully air-gapped systems for intelligence analysis, report generation, and operational planning.

Law Firms

Client confidentiality and NDA requirements prevent use of cloud AI. Local LLM assists with contract review, legal research, document drafting, and case analysis without data risk.

Healthcare

Patient data under DHA and DOH regulations cannot be processed by external AI. On-premise LLM enables clinical note summarization, research assistance, and administrative automation.

Enterprise & Conglomerates

Large organizations with sensitive IP, trade secrets, and proprietary data. Deploy AI assistants across your organization without any data leaving the corporate network.

Technical Details

Prometheus + Grafana monitoring, full audit logging, and optional high-availability failover.

Local inference
Chat interface
Air-gapped ready
SSO / LDAP
GPU & CPU support
Audit logging
# Deployment Architecture

Server Requirements:
  GPU:     NVIDIA A100 / RTX 4090 / Apple M-series Ultra
  RAM:     64GB+ (128GB recommended)
  Storage: 500GB SSD
  Network: LAN only (no internet required)

Software Stack:
  Inference:  Local engine (GPU-optimized)
  Frontend:   Browser-based chat interface
  Auth:       SAML 2.0 / LDAP / Active Directory
  Monitoring: Prometheus + Grafana
  Logging:    Full audit trail (who asked what, when)

Model Options:
  General:    Llama 3.3 70B, Qwen 2.5 72B
  General/Code: DeepSeek V3
  Arabic:     Jais, ALLaM
  Legal:      Fine-tuned variants available

Performance:
  Concurrent users: 10-50 (model dependent)
  Response time:    1-5s (first token)
  Context window:   up to 128K tokens

Every project is different

Pricing depends on your infrastructure, number of users, and integration requirements. We'll assess your setup and propose a solution that fits your budget and timeline.

Ready to deploy AI on your infrastructure?

Tell us about your requirements and we'll propose a solution. Free initial consultation.

See RAG Service