We deploy state-of-the-art language models directly on your infrastructure — giving your team the power of GPT-4 class AI while keeping every byte of data inside your security perimeter.

How Private LLMs Protect Your Data

• Zero data egress — every prompt, response, and intermediate computation happens on hardware you control. No API calls leave your network
• No third-party data retention — unlike cloud AI providers, there is no vendor retaining your prompts for model improvement or any other purpose
• Air-gapped deployment options — for the most sensitive environments, we deploy AI systems with zero internet connectivity
• Open-source transparency — every component is auditable. No black boxes, no hidden data collection, no proprietary backend you cannot inspect
• Full audit trail — comprehensive logging of every AI interaction, who accessed what, when, and what data was processed

Data sovereignty means your data is processed and stored only in locations you control, under legal jurisdictions you choose. Cloud AI providers process your data in data centers across multiple countries — often without your knowledge or consent.

Our Data Sovereignty Guarantee

• Geographic control — your AI processes data only in your facilities, in your state, under your chosen legal jurisdiction
• No cross-border data transfers — eliminates GDPR Schrems II concerns and data residency requirements
• Hardware ownership — you own the servers, the GPUs, the storage. No shared infrastructure, no multi-tenant risks
• Encryption everywhere — AES-256 encryption at rest, TLS 1.3 in transit, and encrypted model weights on disk
• Data lifecycle management — clear policies for data retention, archival, and destruction that satisfy auditor requirements

Traditional encryption protects data at rest and in transit — but leaves it exposed during processing. Confidential computing extends protection to data while it is being actively used by the AI model.

How We Implement Confidential Computing

• Hardware-level isolation — NVIDIA Trusted Execution Environments (TEEs) and AMD SEV create hardware-enforced isolation that prevents even root-level access to data during processing
• Encrypted memory — data remains encrypted even in GPU memory during inference, protecting against physical and software-based attacks
• Attestation — cryptographic proof that the AI workload is running in a genuine secure enclave, verified before any data is processed
• Zero-trust architecture — no component trusts any other component by default. Every interaction is authenticated, authorized, and logged

Our private AI deployments are designed from the ground up to satisfy the data privacy requirements of major regulatory frameworks. Here is how our approach maps to each.

AI data privacy isn’t just a technical challenge — it’s a regulatory, legal, and operational challenge. We bring all three disciplines together.

• 23+ years in cybersecurity — data protection is our core business, not an afterthought bolted onto an AI practice
• Licensed digital forensics examiners — we understand data exposure at a forensic level, which informs how we architect AI privacy controls
• CMMC Certified Registered Practitioner — we build to the most demanding data handling standards from day one
• Zero breaches among compliant clients — our security track record speaks for itself
• Full-stack capability — we deploy and manage the entire AI and security infrastructure, eliminating gaps between vendors