Zero data egress · Private LLM · Regulatory compliance
Your data stays in-house. Your AI capability doesn’t have to.
Sovereign AI is an approach to AI deployment that keeps sensitive data out of external clouds and third-party LLM APIs, running a private LLM inside your own infrastructure (on-prem) or VPC to secure data sovereignty and regulatory compliance. TreeSoop has shipped on-prem AI into air-gapped environments in manufacturing, aerospace, and enterprise HR, and builds regulation-ready AI with zero data egress, PII masking, and audit logging — rated 4.92/5 on Wishket, Korea’s largest dev-outsourcing platform.
The moment internal documents, personal data, or trade secrets are sent to an external cloud or a commercial LLM API, you lose data sovereignty and take on leakage and misuse risk.
In finance, healthcare, and the public sector, regulations — electronic-finance supervision rules, medical-data protection, mandated network separation — prohibit sending data outside or even connecting to the internet, ruling out ordinary cloud AI.
Data sent to external LLM APIs may be reused for model training or retained in logs — making it hard to entrust sensitive data from a contractual and audit standpoint.
We deploy a private LLM on your own servers or inside an isolated VPC, so the entire inference and retrieval pipeline runs exclusively within your infrastructure. Fully air-gapped, internet-disconnected deployments are supported.
Automatic PII redaction, full audit logging of every prompt and response, and role-based access control (RBAC) — a layered security setup that satisfies regulatory audit requirements.
We design the architecture and data flows around your industry’s regulatory requirements — electronic finance, medical-data protection, public-sector network separation — and support the compliance documentation as well.
We fine-tune open-source LLMs such as Llama and Qwen on your domain data, then quantize and compress them to fit your in-house GPU resources — production-grade performance without any commercial API.
We assess your security requirements — regulations, network separation, data classification — along with available infrastructure (GPUs, servers), and lock in the deployment architecture direction.
We design the security architecture: on-prem or VPC deployment structure, private LLM selection, PII masking, audit logging, and access control.
We deploy the private LLM and pipeline onto your infrastructure, verify zero data egress, and tune for performance and accuracy.
We prepare compliance documentation and audit-response materials, then hand over the operations and monitoring setup to your team.
An air-gapped AI system that processes DXF drawings entirely on-prem — under NDA and a strict no-egress policy — to extract BOMs automatically
An on-prem quotation-automation AI that matches similar quotes and maps parts entirely within the company’s own infrastructure
An air-gapped HR and training AI agent that never sends employee personal data or HR records outside the company
0
Data egress
Sensitive data never leaves your infrastructure
3
On-prem deployments
Air-gapped delivery track record in manufacturing, aerospace, and enterprise HR
Llama · Qwen
Open-source private LLMs
Fine-tuned, optimized stack for in-house deployment
Air-gapped
Network separation
Deployment supported in internet-disconnected environments
Our experts will recommend the best approach for your project.
