We build private AI platforms for organizations in government, defense, healthcare, and financial services, where the cost of getting data security wrong isn't a fine. It's an existential threat.
We pre-fill Calendly so you can grab a 30 or 45 minute slot in one step. No extra landing pages.
The same architecture is already running real work for nBrain clients, including a Tier 2 defense manufacturer.
Regal Technology Partners has shared its story publicly. Other results are anonymized to protect client confidentiality. Read the customer stories
Organizations in government, healthcare, and finance face the same choice every day: adopt AI and risk breaking compliance requirements, or avoid AI and fall behind the competitors who worked out how to do it safely.
ChatGPT, Copilot, and consumer AI tools send your data to third-party servers. For organizations handling CUI, PHI, or regulated financial data, that breaks nearly every compliance framework you operate under.
SaaS platforms adding AI features process your data on their infrastructure, with their models, under their terms. You don't own the intelligence, you can't audit the pipeline, and your data may be training their models.
A compliant AI platform takes LLM architecture, vector databases, retrieval pipelines, zero-retention API design, and regulatory frameworks. That combination is rare to find in one team.
The organizations that need AI most, the ones buried in documents, compliance requirements, and manual processes, are the ones least able to adopt it.
nBrain builds custom AI platforms that run entirely inside your perimeter: your cloud tenant, your data center, or an air-gapped network. We don't host your data and we don't train models on it. We build the platform in your infrastructure and hand you the keys, so your data never crosses a boundary you don't control.
We build the intelligence around the model: the agents, the retrieval logic, the workflows, the permissions. We never put your data inside the model. The AI reads your documents at query time, writes an answer, and forgets. Your data stays in your environment and the model stays generic. That's the architecture that makes compliance possible. What a Centralized AI Brain is →
Every regulated industry has its own set of compliance requirements. We build AI platforms designed to support them, not by avoiding data, but by architecting around the rules.
Defense contractors, government agencies, and intelligence-community suppliers need AI that handles CUI, ITAR data, and classified-adjacent information without exposing it to commercial cloud infrastructure or third-party models.
We deploy inside your Azure Government tenant, which carries FedRAMP High and DoD IL4/IL5 authorizations, with private endpoints, VNet isolation, and US-only data residency.
Organizations handling PHI need AI that never stores, sends, or processes patient data outside a HIPAA-compliant environment. We build platforms that work with clinical data while maintaining full BAA coverage.
PHI-aware processing strips, tokenizes, or masks identifiers before data reaches any model. Your BAA with the cloud provider covers the entire pipeline.
Banks, asset managers, insurers, and fintech firms work under some of the strictest data-handling rules in business. AI platforms here need full audit trails, explainable outputs, and no data leakage.
We build systems with complete lineage tracking, so every AI response can be traced back to its source documents for a regulatory examination.
Every private AI platform we build follows the same pattern: capture your institutional knowledge in one AI Brain first, then attach specialized modules that read from it, write to it, and make it smarter with every interaction, all inside your security perimeter.
We map your data: where documents live, which systems feed your operations, which data classifications apply, and which frameworks govern your environment. We sort what can be processed now from what needs specific infrastructure.
Weeks 1–2We deploy the platform in your cloud subscription: Azure Government, AWS GovCloud, or private infrastructure. Private endpoints, VNet isolation, and encryption at rest and in transit. Your IT team controls the keys.
Weeks 2–4Documents are ingested, chunked, embedded, and stored in your vector database. We build the retrieval pipeline that finds the right documents when your team asks a question. The model never learns this data; it reads it at query time and forgets.
Weeks 3–6We build the agents and modules on top of the Brain: document search, summarization, compliance analysis, proposal drafting, or whatever matters most to your operations. Role-based access means people see only the data they're authorized for.
Weeks 5–8You own the subscription, the source code, and the infrastructure configuration. We support you for as long as you want us, and you can bring in your own team at any time. No vendor lock-in, and your data is never held hostage.
Weeks 8–12A typical build takes about three months. Builds start at $40,000, and your cloud and model accounts are billed to you directly at list price, with no markup.
The platform architecture is designed to support several regulatory frameworks at once. Here is how each component maps to the requirements you face.
| Architecture component | Government / defense | Healthcare | Financial |
|---|---|---|---|
| Zero data retention by the AI model | CMMC / ITAR | HIPAA | GLBA / SOX |
| Encryption at rest (AES-256) | NIST 800-171 | HIPAA Security Rule | PCI DSS |
| Encryption in transit (TLS 1.3) | DFARS 7012 | HIPAA Security Rule | PCI DSS |
| Role-based access control | NIST AC controls | Minimum necessary | SOX / FINRA |
| Tamper-evident audit logging | NIST AU controls | HIPAA audit requirements | SOX Section 302 |
| US-only data residency | ITAR / FedRAMP | BAA territory | Data sovereignty |
| MFA enforcement | CMMC Level 2 | HIPAA access controls | FFIEC guidance |
| Source citation on every response | Verification requirements | Clinical accuracy | Regulatory examination |
The matrix shows which requirement each component is built to support. It isn't a certification: nBrain doesn't hold FedRAMP, CMMC, HITRUST, or SOC 2 attestations. The platform deploys inside the environment you have already authorized and assessed. Read the security overview →
These aren't marketing claims. They're architectural guarantees, backed by the platform design, cloud provider contracts, and our engagement terms.
Cloud providers offer zero data retention where available, and no model training on your data on your inputs and outputs.
Each query is an independent API call. The model keeps nothing between calls: no session, no memory, no learning.
The subscription, the code, the infrastructure, and the data. You can bring in your own team or another vendor at any time.
Private endpoints, VNet isolation, and zero internet egress. API calls stay inside your cloud provider's sovereign infrastructure.
Every query, document access, and AI response is logged with tamper-evident audit trails that feed your SIEM.
Switch between GPT-6 Astra, Claude Opus 5.5, Gemini 4 Argon, or on-premises open-source models without rebuilding. Your Brain stays; the engine is replaceable.
Private AI platforms delivered for organizations working under some of the most demanding regulatory environments there are.
Built for a Tier 2 defense supplier handling CUI and ITAR data . Azure Government deployment with a design that supports CMMC Level 2, NDA-compliant architecture, and role-based access separated by program clearance.
Result: AI document search, engineering spec analysis, and accounts payable automation, all inside their security perimeter.
A technical guide for healthcare organizations adopting AI under HIPAA: compliant model selection, BAA requirements, PHI handling architecture, PII tokenization, and workable use cases across clinical operations.
Resource: written for healthcare leaders evaluating a private AI deployment.
Designed and scoped an accounts payable platform that extracts invoice data, matches it against purchase orders, flags discrepancies, and routes approvals, with complete audit trails for SOX and internal-control requirements.
Result: invoices moved from a shared mailbox to approval, with a person approving every one with full compliance auditability.
If this architecture can handle a defense manufacturer's most sensitive programs under ITAR and CMMC, it can handle your compliance requirements.
An executive briefing for leaders adopting AI under regulatory constraints. No vendor spin: the architecture decisions, compliance boundaries, and implementation strategies that work.
While competitors wait for permission, we build you a private AI platform that works inside your rules. In one strategy session we show you what's possible in your regulatory environment.
Prefer email? hello@nbrain.ai