Generative AI is rapidly transforming knowledge work. Yet in highly regulated industries, the most powerful models remain largely unusable. Automotive manufacturers, suppliers, and legal professionals operate under strict data protection, intellectual property, and compliance constraints. For them, sending sensitive prompts and regulatory material to public AI platforms is not a viable option.
This structural barrier — the need for full control over data, infrastructure, and outputs — has limited the practical adoption of generative AI in legal and homologation environments. Today, we are publishing our white paper on a different approach: The Air-Gapped Legal Mind.
Why Cloud-Based AI Is Not Enough for Regulated Work
Large language models are probabilistic systems. While powerful, they are inherently non-deterministic and may generate hallucinated statements or citations. In regulated domains such as automotive homologation, a subtle misinterpretation of a regulatory threshold can have material financial and legal consequences.
At the same time, transmitting proprietary engineering data or compliance strategies to external AI providers introduces sovereignty and confidentiality risks that many organizations cannot accept.
The question is therefore not whether AI is useful — but how it can be deployed safely and responsibly in regulated environments.
A Sovereign Architecture for Legal AI
The Air-Gapped Legal Mind proposes a clear architectural principle: Separate reasoning from knowledge, and operate both within controlled local infrastructure.
Instead of relying on hyperscale cloud models, the system combines:
Local Micro-LLMs (7–8B parameter models) for structured reasoning
Retrieval-Augmented Generation (RAG) to ground responses in authoritative documents
Infrastructure physically isolated from external networks
This design ensures that sensitive regulatory corpora remain under organizational control while maintaining high precision and auditability.
Large-Scale Validation: EU and UNECE Regulatory Corpus
To test this architecture in practice, we indexed:
257,000+ European Union legislative documents from EUR-Lex
1,000+ UNECE vehicle regulations, including Regulation No. 157 (ALKS)
The deployment addressed key RAG engineering challenges, including conversational context loss, acronym resolution in technical regulation, and retrieval bias in geographically referenced queries.
The results demonstrate that properly engineered local systems can meet the precision requirements of professional homologation and legal workflows — without relying on public AI APIs.
From Prototype to Enterprise Deployment
The white paper also analyzes the hardware and economic implications of sovereign AI.
We examine:
Prototyping on local workstation-class systems (e.g., Apple Silicon)
Enterprise scaling using GPU-accelerated infrastructure
A five-year Total Cost of Ownership comparison between on-premise CapEx and cloud-based OpEx models
Under sustained utilization, locally operated infrastructure can provide both cost predictability and full intellectual property control.
Why This Matters Now
Regulated industries face increasing pressure to modernize compliance processes while maintaining strict governance standards. Sovereign AI architectures provide a path forward: enabling automation, structured retrieval, and advanced reasoning without compromising data protection or professional accountability.
The Air-Gapped Legal Mind is not a theoretical concept. It is a tested architecture designed for real-world regulatory environments.
Download the White Paper
We are making the full technical white paper available for download.
It includes:
Architectural design principles
Engineering controls for regulatory-grade RAG
Infrastructure benchmarking
Economic modeling (CapEx vs. OpEx)
Governance and auditability framework
📄Download the white paper by clicking this link.
For organizations interested in evaluating the approach, we also provide an open reference package (CORA: Air-Gapped Legal AI (Lite Edition)) for local benchmarking.
For inquiries, please contact: [email protected].