Own Your AI.
Don't Rent It.
Enterprise-grade private AI systems designed, deployed, and secured in-house. No vendor lock-in. No data leakage. No compromise.
The AI Risk Problem
Every enterprise deploying AI through third-party SaaS platforms is making a bet—that their proprietary data, competitive intelligence, and operational logic will remain secure inside someone else's infrastructure. That bet is losing.
In 2025 alone, major AI providers experienced data exposure incidents affecting millions of enterprise records. Model training on customer data—whether disclosed or not—means your competitive advantage is being absorbed into systems your competitors also use. Your prompts, your data pipelines, your business logic: all flowing through infrastructure you don't control, can't audit, and can't secure.
Data Exposure
Your proprietary data trains models that serve your competitors. Every API call is a potential leak.
Compliance Failure
HIPAA, CMMC, FedRAMP, PCI-DSS—none of them were designed for data flowing through shared AI infrastructure.
Vendor Lock-In
Proprietary APIs, opaque pricing, unilateral model deprecation. Your AI strategy is hostage to someone else's roadmap.
Operational Fragility
Rate limits, outages, policy changes. When your AI goes down, your operations go with it.
Why SaaS AI Is Not Enough
SaaS AI platforms are designed for convenience, not sovereignty. The trade-offs are structural—not fixable with better contracts or enterprise tiers.
| Dimension | SaaS AI | Sovereign AI (Askbuc) |
|---|---|---|
| Data Residency | Vendor-controlled, multi-tenant | Your facility, your jurisdiction |
| Model Training | Your data may train shared models | Your data trains only your models |
| Compliance | Shared responsibility, limited audit | Full audit trail, air-gap capable |
| Availability | Subject to vendor outages & rate limits | 99.99% SLA under your control |
| Cost at Scale | Per-token pricing compounds rapidly | Fixed infrastructure, unlimited inference |
| Customization | Limited fine-tuning, no architecture control | Full model selection, training, and tuning |
| Exit Strategy | Proprietary APIs, high switching cost | Open standards, portable architecture |
What Sovereign AI Means
Sovereign AI is not a marketing term. It is an architecture decision. It means your organization owns every layer of the AI stack—from silicon to inference—and no external entity can access, modify, or revoke your capabilities.
Physical Sovereignty
Your hardware. Your facility. Your jurisdiction. GPU clusters, storage arrays, and networking equipment under your physical control—or in a facility you audit and approve.
Model Sovereignty
Your models. Your weights. Your training data. Fine-tuned on your proprietary corpus, running inference without external API calls. No vendor can deprecate your capabilities.
Operational Sovereignty
Your policies. Your access controls. Your audit trail. Every inference logged, every access authenticated, every data flow encrypted end-to-end with keys you control.
Our Deployment Methodology
A disciplined, phased approach refined across 25+ years of enterprise infrastructure delivery.
Discovery & Architecture Audit
2–4 WeeksWe assess your current infrastructure, data landscape, compliance requirements, and AI objectives. Deliverable: a detailed architecture blueprint with risk assessment, cost model, and implementation timeline.
Infrastructure Design & Procurement
4–8 WeeksHardware specification, vendor negotiation, facility preparation. GPU cluster sizing based on your workload profiles. Network topology designed for zero-trust segmentation. Power and cooling engineered for sustained compute loads.
Deployment & Model Integration
4–12 WeeksPhysical installation, OS hardening, container orchestration, model deployment. Your selected models—open-source or proprietary—fine-tuned on your data. RAG pipelines, vector databases, and inference endpoints configured and tested.
Security Hardening & Compliance
2–4 WeeksPenetration testing, vulnerability assessment, compliance validation. NIST 800-53, CMMC, HIPAA, PCI-DSS—whatever your regulatory framework requires. Air-gap configuration for classified environments.
Autonomous Agent Deployment
4–8 WeeksCustom AI agents designed for your workflows. Document processing, decision support, operational automation, customer interaction—each agent built with guardrails, monitoring, and human-in-the-loop controls.
Ongoing Operations & Optimization
Continuous24/7 monitoring, model retraining, performance optimization, capacity planning. Your AI infrastructure evolves with your business. Quarterly architecture reviews ensure you stay ahead of the curve.
Infrastructure Tiers
Three engagement levels calibrated to organizational scale, regulatory requirements, and AI maturity.
Starter
AI readiness assessment, architecture blueprint, and proof-of-concept deployment for organizations beginning their sovereign AI journey.
- Infrastructure audit & gap analysis
- Architecture blueprint & cost model
- Single-model PoC deployment
- Security baseline assessment
- 90-day implementation roadmap
Professional
Complete private AI infrastructure deployment with multi-model support, autonomous agents, and ongoing optimization for mid-market enterprises.
- Everything in Starter, plus:
- Multi-model deployment (LLM + Vision + Code)
- Custom autonomous agent development
- RAG pipeline with vector database
- Compliance hardening (HIPAA/PCI/CMMC)
- 6-month support & optimization
Sovereign
Full sovereign AI architecture for large enterprises, government agencies, and regulated industries requiring air-gapped, fully auditable AI systems.
- Everything in Professional, plus:
- Air-gapped deployment capability
- Custom model training on proprietary data
- Multi-site redundancy & failover
- FedRAMP/NIST 800-53 compliance
- Dedicated 24/7 AI operations team
- Quarterly architecture reviews
Security Architecture
Every layer hardened. Every access authenticated. Every byte encrypted.
Zero-Trust Network
Microsegmented networks with continuous authentication. No implicit trust—every request verified, every session monitored.
Post-Quantum Encryption
Crystal Kyber and CRYSTALS-Dilithium algorithms protecting data at rest and in transit against quantum computing threats.
Full Audit Trail
Every inference, every data access, every model interaction logged with tamper-proof integrity. Complete forensic capability.
Air-Gap Capable
Complete network isolation for classified and ultra-sensitive environments. No external connectivity required for operation.
Compliance Framework
Pre-configured for NIST 800-53, CMMC Level 3, HIPAA, PCI-DSS, FedRAMP, SOC 2 Type II, and ISO 27001.
Intrusion Detection
AI-powered threat detection monitoring all network traffic, system calls, and model behavior for anomalous patterns.
Technical Stack
Enterprise-proven components. No experimental dependencies. Production-hardened from day one.
Compute
- NVIDIA H100/H200 GPU Clusters
- AMD MI300X Accelerators
- Intel Xeon Scalable CPUs
- Liquid & Immersion Cooling Systems
Models & Frameworks
- Llama 3.1 / Mixtral / Qwen 2.5
- vLLM / TensorRT-LLM Inference
- PyTorch / JAX Training Pipelines
- LangChain / LlamaIndex Orchestration
Data & Storage
- Milvus / Qdrant Vector Databases
- PostgreSQL + pgvector
- MinIO S3-Compatible Object Storage
- Ceph Distributed Storage Clusters
Infrastructure
- Kubernetes (K8s) Orchestration
- Terraform Infrastructure-as-Code
- Prometheus + Grafana Monitoring
- HashiCorp Vault Secrets Management
Security
- WireGuard / IPsec VPN Tunnels
- CrowdStrike / Wazuh EDR
- Snort / Suricata IDS/IPS
- SIEM Integration (Splunk / Elastic)
Networking
- 25/100GbE InfiniBand Fabric
- BGP/OSPF Routing
- VXLAN Network Segmentation
- DNS-over-HTTPS / DNSSEC
Ideal Client Profiles
We build for organizations where AI is mission-critical—not experimental.
Healthcare Systems
Hospitals, health networks, and pharma companies requiring HIPAA-compliant AI for clinical decision support, medical imaging, and operational automation.
Defense & Government
Federal agencies, defense contractors, and intelligence organizations requiring air-gapped, CMMC/FedRAMP-compliant AI infrastructure.
Financial Institutions
Banks, hedge funds, and insurance companies requiring PCI-DSS compliant AI for fraud detection, risk modeling, and regulatory reporting.
Critical Infrastructure
Energy utilities, water systems, and transportation networks requiring NERC CIP-compliant AI for SCADA monitoring and predictive maintenance.
Law Firms & Professional Services
Am Law 200 firms and consulting practices requiring confidential AI for document review, research, and client-privileged analysis.
Manufacturing & Logistics
Industrial operations requiring on-premise AI for quality control, supply chain optimization, and predictive maintenance at the edge.
Who We Don't Work With
We are not a chatbot agency. We are not an MSP break/fix shop. We are not SaaS AI consultants. Our engagements are designed for serious organizations with:
- Regulatory or compliance requirements that prohibit shared AI infrastructure
- Proprietary data that represents genuine competitive advantage
- AI workloads that justify dedicated compute resources
- Executive sponsorship and commitment to long-term AI capability
- A 12+ month horizon for AI strategy—not a weekend prototype
Regional Healthcare Network: From SaaS Dependency to Sovereign AI
The Challenge
A 12-hospital healthcare network was using a major cloud AI provider for clinical decision support, medical imaging analysis, and patient communication automation. After a vendor policy change allowed training on customer data, the organization's HIPAA compliance posture was compromised. Simultaneously, per-token costs had escalated dramatically with no performance improvement.
The Solution
Askbuc deployed a Sovereign-tier private AI infrastructure across two geographically separated data centers. The system included 8x NVIDIA H100 GPUs, a fine-tuned Llama 3.1 70B model trained on 2.3 million de-identified clinical records, and a RAG pipeline connected to the organization's Epic EHR system. Air-gapped network segments ensured PHI never left the organization's control.
The Outcome
Within 6 months, the healthcare network had eliminated its SaaS AI dependency entirely. Clinical decision support accuracy improved by 18% due to fine-tuning on proprietary data. The organization now runs unlimited inference at a fixed monthly cost, with complete audit trail for regulatory compliance. First-year savings exceeded seven figures.
Details modified to protect client confidentiality under NDA. Representative of typical engagement outcomes.
AI Sovereignty Readiness Checklist
10 diagnostic questions every executive should answer before committing to an AI strategy. Assess your organization's readiness for sovereign AI infrastructure in under 10 minutes.
Request ChecklistSample Questions
- 1.Does your AI vendor's terms of service permit training on your data?
- 2.Can you audit every inference made on your proprietary information?
- 3.What happens to your AI capabilities if your vendor raises prices 300%?
- 4.Are your AI workloads compliant with your industry's regulatory framework?
- 5.Do you have a documented exit strategy from your current AI provider?
+ 5 additional diagnostic questions in the full checklist
Your AI. Your Infrastructure.
Your Competitive Advantage.
Stop renting intelligence. Start owning it. Schedule a confidential architecture review with our senior engineering team.