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Private LLM & Secure RAG

A focused guide series for regulated and GovCon teams who need enterprise AI over sensitive data without losing control of the model, the retrieval path, or the evidence. Start with what a private LLM is, then move into deployment, retrieval, and leakage controls for secure AI automation.

Why This Series Matters

Private is not a product you buy. It is a set of controls you can prove. This series helps leaders connect the model environment, deployment options, retrieval design, and leakage prevention into one defensible approach for CUI and other high value data.

Best Starting Point

What Is a Private LLM?

Start with the definition, then use the supporting guides to choose a deployment option, design secure retrieval, and keep controlled information out of the wrong lanes.

Read the Main Guide

01Define the control boundary

Understand what makes an LLM private: environment, network path, retention, and logs you can prove.

02Choose a deployment option

Match on prem, self hosted, dedicated tenant, or zero retention lanes to your data class and cost.

03Design secure retrieval

Build permission aware RAG so the model never sees content a user is not allowed to see.

04Prevent leakage

Keep CUI and controlled information out of unapproved paths with classification, gateways, and monitoring.

Featured Guides

Read the Private LLM & Secure RAG Series

Abstract representation of a private large language model running inside a controlled environment

Pillar Guide | Secure AI Automation

What Is a Private LLM?

A private LLM is not a product you switch on. It is a control decision. This guide explains what a private LLM is, when a private LLM is worth the effort, and the controls that make one defensible for regulated and GovCon work.

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Supporting Guide | Secure AI Automation

Private LLM Deployment Options

There is no single private LLM you can buy. There are deployment options, each trading control against cost. This guide compares on prem, self hosted, dedicated tenant, and zero retention lanes, and shows how to match the option to your data.

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Code on a monitor representing secure RAG architecture, enterprise retrieval, and controlled AI systems

Supporting Guide | Secure AI Automation

Secure RAG Architecture for GovCon

A practical guide to secure RAG architecture for GovCon teams that need enterprise AI over internal knowledge without breaking permissions, CUI boundaries, audit trails, or data controls.

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Secure laptop and network equipment representing controlled LLM data paths for CUI protection

Supporting Guide | Secure AI Automation

Preventing CUI Leakage in LLMs

A practical GovCon guide to keeping CUI out of unapproved LLM paths by controlling prompts, uploads, RAG, vector databases, logs, vendors, and downstream workflow tools.

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AI system architecture concept representing public private and hybrid AI deployment choices

Supporting Guide | Secure AI Automation

Private AI vs Public AI vs Hybrid AI Automation

A practical guide for regulated organizations choosing between public AI, private AI, and hybrid AI automation based on data sensitivity, workflow risk, AI authority, and evidence requirements.

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Need a private LLM your security team can approve?

GS Consulting helps regulated and GovCon teams classify data, choose deployment options, design secure RAG, prevent CUI leakage, and build the evidence packet assessors will ask for.

Request a Private LLM Readiness Review