Private AI for the defense industrial base

Your DIBCAC assessor will ask about AI. We built the answer.

A private AI platform deployed inside your Azure Government CUI enclave, your own data center, or a fully air-gapped network. No data egress. No model training on your data. A control mapping to the NIST SP 800-171 families, ready for your SSP. Already deployed for a Tier 2 defense supplier handling ITAR program data.

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Built for ITAR, CUI, and CMMC environments Designed to support CMMC Level 2 and NIST SP 800-171 Runs fully air-gapped if your program needs it

The DIB problem Architecture NIST mapping

Discovery call

Quick details, then pick a time

Four fields. We pre-fill Calendly so you can grab a 30- or 45-minute slot in one step. No extra landing pages.

The same platform is already running real work for nBrain clients, including a Tier 2 defense manufacturer.

92%

less sales-team time on RFQs at Regal Technology Partners, a Tier 2 defense manufacturer

5 months

from first idea to a Brain built and launched across a 200-person manufacturer

65%

lower cost per AI task through model routing

33.5%

average increase in employee productivity within six months

Regal Technology Partners has shared its story publicly. Other results are anonymized to protect client confidentiality. Read Regal's story

The DIB's AI problem

Why most defense suppliers conclude they can't use AI, and why they're wrong.

Defense suppliers are caught in a three-way bind: commercial tools, prime contract terms, and CMMC. Each one is real. None of them is a ban on AI.

Commercial AI is a non-starter

ChatGPT, Copilot, and consumer tools process data on servers outside your boundary. For CUI or ITAR technical data, one paste can be a DFARS violation, an NDA breach, and potentially an unlicensed export, all at once.

Your prime's NDA looks like a ban

Section 3.1.6 prohibits AI use "in a manner that does not comply with disclosure restrictions." Most legal teams read that and stop. But the clause doesn't ban AI. It bans AI that breaks confidentiality.

CMMC adds another layer

Adding AI means updating your SSP, addressing NIST SP 800-171 control families, and possibly opening POA&M items. Without an architecture built for CMMC, AI becomes a compliance liability.

Your competitors are moving

While your team searches PLM systems by hand for spec revisions, competitors are deploying AI inside their enclaves, answering engineering questions in seconds with source citations.

Architecture

AI that lives inside your CUI enclave.

Your CUI never leaves your security boundary, and the model never trains on your data. The Brain, its knowledge, and its audit trail sit inside the boundary you have already built and assessed.

Your CUI enclave · Azure Government

Everything that knows your business

AI Brain: your institutional knowledge, agents, and workflows
Vector database: encrypted, with no egress path
Audit trail: streamed to your SIEM, tamper-evident
Role-based access: program-level data segregation and US-person checks
Source code: you own all of it

Pre-trained model endpoint

Reasoning, with no memory of you

Pre-trained on public data only
Stateless: no memory between queries
Your data never modifies the model
No training on your data, under Microsoft's data processing terms
US government cloud regions only, reached through private endpoints

FedRAMP High

Azure Government authorization

DoD IL4 / IL5

Azure Government regions

800-171

Control families mapped

No egress

CUI stays in your boundary

FedRAMP High and DoD IL4/IL5 are Microsoft's authorizations for Azure Government, which your tenant inherits. nBrain holds no FedRAMP, CMMC, or Impact Level authorization of its own.

Option 01 · Government cloud

Your Azure Government or GovCloud tenant

The architecture above. The Brain runs under your accounts, your keys, and your authorization, with frontier models such as GPT-6 Astra reached through government-cloud endpoints you approve.

Option 02 · On-premises

Your data center, your hardware

Installed on servers and GPUs you own, behind your firewall, managed under the controls you already run. Internet isn't required for daily use.

Option 03 · Fully air-gapped

Disconnected, no outbound internet

Open-weight models (Llama, Mistral, Qwen) run locally on your GPUs. Air-gapped deployment is scoped per program.

The trade-off, stated plainly

GPT-6 Astra, Claude Opus 5.5, and Gemini 4 Argon are hosted services, so they can't run on a network with no internet. An air-gapped Brain uses open-weight models instead. They handle search, cited answers, summaries, and first drafts well, but can trail frontier models on the hardest multi-step reasoning, so we test them on your own documents before go-live. Compare all three deployments →

What we cover on a 30–45 minute call

A focused discovery session, not a slide deck.

With engineers who have deployed private AI inside Azure Government for ITAR-controlled programs.

Your current architecture reviewWe map where your CUI enclave stands today and find the gaps before AI enters the picture.
NIST SP 800-171 AI control mappingSee how AI maps to the AC, AU, SC, MP, IA, IR, and CM control families in your SSP.
NDA clause analysisWe show why the AI clause in your prime's NDA doesn't ban AI, and give you clarification language for your prime.
Real deployment walkthroughSee the platform we built for a Tier 2 defense supplier working on ITAR-controlled programs.
Parallel strategy roadmapStart with non-CUI use cases now, such as AP automation and financial analysis, while your enclave finishes standing up.

Deployed under ITAR and CMMC constraints

We deployed this architecture for a Tier 2 defense supplier handling ITAR program data. Same boundary, same NIST SP 800-171 controls.

nBrain AI Schedule discovery call

NIST SP 800-171 control mapping

The mapping your assessor will want to see.

How the AI platform addresses each control family. Built into the architecture, and written up for your SSP.

Control family	How the AI platform addresses it	Source
AC · Access Control	Role-based access through Entra ID, MFA, Conditional Access, and program-level data segregation.	Platform design
AU · Audit and Accountability	Tamper-evident logging into Sentinel SIEM, with a 90-day minimum retention.	Platform design
SC · System and Communications Protection	TLS 1.3, AES-256, private endpoints, VNet isolation, and no data egress.	Platform design
MP · Media Protection	Encrypted embeddings, kept inside the Azure Government boundary, with no export paths.	Platform design
IA · Identification and Authentication	Entra ID with MFA, PIM for admin roles, and certificate-based device authentication.	Platform design
IR · Incident Response	Defender for Cloud, query anomaly detection, and a 72-hour DFARS reporting workflow.	Platform design
CM · Configuration Management	Azure Policy, infrastructure-as-code, and change tracking.	Platform design
PE · Physical Protection	Azure Government data centers: FedRAMP High, DoD IL4/IL5, US only.	Inherited from Azure

What we do and don't claim. nBrain doesn't hold a FedRAMP authorization, a CMMC certification, or a DoD Impact Level authorization, and there is no such thing as an ITAR certification. The platform is built for ITAR-controlled and CUI environments and deploys inside a boundary you have already authorized and assessed. Your ISSO approves the write-up, and your C3PAO makes the call.

Go deeper. The framework-by-framework view covers ITAR and EAR, DFARS 7012, CMMC Level 2, FedRAMP, Impact Levels, and SPRS. See the compliance breakdown →

See it on your programs

Your SSP already has 110 controls. Adding AI shouldn't create 110 more problems.

We've done the NIST mapping. We've been through the NDA scrutiny. We've built the architecture. In one session we'll walk you through it and map where a private Brain would give your team time back first.

Book a strategy session

Want a discovery call with an engineer instead? Pick a 30–45 minute slot · or email hello@nbrain.ai