Why Private AI
Cloud AI services are convenient, but they require sending your data to someone else's servers. For businesses handling sensitive client information, proprietary data, regulated records, or classified material, that is a non-starter. Private AI deployment puts the full power of modern language models inside your own infrastructure, where you control every byte.
On-Premises LLMs
Run open-weight models on your own hardware. Full capability of frontier-class models with zero data exfiltration risk. We handle model selection, quantization, and optimization for your specific hardware.
Private Cloud Deployment
Deploy AI within your own VPC on AWS, Azure, or GCP. Your models run on dedicated instances with no shared tenancy. Data stays within your cloud boundary, satisfying compliance requirements while leveraging cloud scalability.
Air-Gapped Systems
For the most sensitive environments, we deploy AI systems with no internet connectivity whatsoever. Defense contractors, government agencies, and financial institutions with strict isolation requirements. Models run entirely offline.
Secure Inference Pipeline
End-to-end encryption, audit logging, access controls, and data retention policies built into the inference layer. Every prompt and response is tracked, and you define exactly who can access what.
Deployment Architecture
Assess
Security, compliance, data sensitivity
Design
Choose deployment model
Deploy
Models on your infrastructure
Secure
Encryption, audit, access control
Monitor
GPU utilization, latency, cost
Assess
Security, compliance, data sensitivity
Design
Choose deployment model
Deploy
Models on your infrastructure
Secure
Encryption, audit, access control
Monitor
GPU utilization, latency, cost
Private AI Deployment Services
Deployment Models
We design private AI infrastructure across a spectrum of isolation levels. The right choice depends on your regulatory requirements, data sensitivity, and operational needs.
Dedicated cloud instances. AI models running on reserved compute in your own VPC. No shared hardware, no data leaving your cloud account. This is the fastest path to production for most organizations and supports auto-scaling for variable workloads.
On-premises GPU servers. For organizations that require physical control over their infrastructure. We specify, configure, and deploy GPU servers in your data center running optimized inference engines. Typical hardware: NVIDIA A100/H100 clusters with NVLink for multi-GPU inference.
Hybrid architecture. Route sensitive workloads to private infrastructure while using cloud APIs for non-sensitive tasks. Intelligent routing based on data classification means you get the cost efficiency of cloud AI where appropriate and the security of private deployment where required.
Edge deployment. AI models running on local hardware at branch offices, factory floors, or field locations. Low-latency inference without network dependency. We optimize models for the target hardware, from enterprise GPUs down to embedded devices.
Areas of Focus
Depending on your requirements and scope, engagements typically cover some or all of the following areas:
- Hardware specification and procurement guidance. GPU selection, memory sizing, networking requirements, and vendor recommendations based on your workload profile.
- Model selection and optimization. Benchmarking open-weight models against your specific use cases and optimizing for your hardware through quantization, pruning, and fine-tuning.
- Inference infrastructure. Production-grade model serving with load balancing, health checks, and scaling, built on proven frameworks like vLLM, TGI, or Triton.
- Security and compliance layer. Authentication, authorization, audit logging, and encryption designed around frameworks like HIPAA, SOC 2, FedRAMP, and ITAR as applicable.
- Monitoring and observability. Visibility into GPU utilization, inference latency, throughput, error rates, and cost per query.
- Knowledge transfer and documentation. Helping your team learn to operate, maintain, and extend the system with documented architecture decisions and operational procedures.
Industries We Serve
Private AI deployment is essential for organizations where data sovereignty is not optional.
Healthcare. Patient records, clinical notes, and diagnostic data processed by AI without HIPAA exposure. On-prem NLP for clinical decision support, medical coding, and administrative automation.
Financial services. Trading signals, risk models, and client data analyzed by AI within your compliance boundary. SOC 2 and regulatory audit trails built in.
Legal. Contract analysis, document review, and legal research powered by LLMs that never see data outside your firm. Attorney-client privilege preserved by design.
Government and defense. Classified and controlled unclassified information processed by AI in air-gapped or IL4/IL5 environments. ITAR and FedRAMP compliancearchitecture.
Manufacturing and IP-heavy industries. Proprietary designs, formulations, and trade secrets analyzed by AI that runs entirely within your facility. No cloud dependency, no data exposure.
Get Started
Private AI deployment starts with understanding your security requirements, data sensitivity, and performance needs. We scope engagements to deliver a working private AI system, not a theoretical architecture document.
Contact us at ben@oakenai.tech to discuss your private AI requirements. We will give you an honest assessment of what is feasible, what it costs, and how long it takes.