Build Your Own AI Infrastructure. Maintain Control of Your Intelligence.
F9 Networks designs and deploys enterprise AI environments that give organizations control over their data, computing resources, AI models, and intelligent applications.
Design, deploy, and operate AI on your terms.
We help organizations implement AI without necessarily relying on expensive third-party cloud AI services.
- On-premise AI infrastructure
- GPU server architecture and deployment
- AI computing clusters
- Private Large Language Model (LLM) deployment
- Open-source AI model deployment
- Local inference environments
- AI agent development and orchestration
- Retrieval-Augmented Generation (RAG)
- Enterprise knowledge management systems
- AI model optimization
- AI infrastructure monitoring
- Hybrid cloud and private AI environments
- AI security and access controls
Private AI. Your Infrastructure. Your Data. Your Control.
Private AI means running models, data pipelines, and AI applications on infrastructure dedicated to your organization, with access and retention policies you define.
Control over sensitive information
Business data, prompts, and outputs can stay on infrastructure you own or control.
Less dependence on external providers
Run open-source and self-hosted models alongside, or instead of, third-party AI services.
Infrastructure sized to your needs
Compute, storage, and networking specified around your workloads and growth plans.
Custom models and agents
Tune models and build agents around your own documents, systems, and processes.
Configurable security and access
Define who can use which models and data, with logging and access policies you set.
Predictable operating costs
Owned or dedicated infrastructure gives you a clearer view of ongoing costs than usage-based billing.
From a single server to a managed AI environment.
The right option depends on your use cases, data sensitivity, user count, and budget. We size each deployment during discovery.
Small business private AI server
A single on-premise server for private chat, document search, and internal assistants.
Enterprise AI workstation and GPU server
Dedicated GPU hardware for teams running larger models, development, and evaluation.
Multi-GPU AI computing cluster
Clustered GPU nodes with shared storage and scheduling for heavier inference and training work.
Fully managed on-premise AI environment
We deploy, monitor, patch, and support the environment on your premises.
Hybrid AI infrastructure
Private infrastructure for sensitive workloads, combined with cloud services where appropriate.
Model performance, hardware requirements, and costs vary with the models, workloads, and data involved. We provide specific sizing and estimates only after assessing your requirements, and we validate performance during deployment rather than promising it up front.
Infrastructure, models, and applications, engineered as one system.
Compute & infrastructure
GPU servers, networking, storage, and monitoring, deployed on your premises, in a colocation facility, or in a hybrid setup.
Models & knowledge
Open-source model selection, private LLM hosting, and RAG pipelines connected to your documents and systems.
Agents & applications
AI agents and applications built by our application development team and secured by our security engineers.
Most projects span more than one discipline.
Ready to plan your private AI environment?
Tell us about your use cases, data, and users. We will recommend a deployment option and outline what it takes to build.