Public Sector AI: Secure, Local, Offline
What is public sector AI?
Public sector AI is the use of artificial intelligence by federal, state, and local government agencies for citizen services, document processing, analysis, and internal operations. Because agency data is often classified, controlled, or personally identifiable, most public sector AI is deployed on premises or air-gapped rather than in a shared commercial cloud.
Transform government operations with AI for government that meets the strictest security requirements. From unclassified to Top Secret environments, Iternal delivers secure local AI and offline AI solutions for federal agencies, defense contractors, and intelligence operations - including AI for SCIFs and air-gapped environments.
What is AI for Government?
Understanding how public sector agencies are adopting artificial intelligence
The State of Public Sector AI in 2025
AI for government is transforming how federal, state, and local agencies operate. According to the U.S. Government Accountability Office (GAO), federal agencies' use of generative AI increased ninefold from 2023 to 2024, with total reported AI use cases nearly doubling from 571 to 1,110 across major agencies.
Public sector AI encompasses a wide range of applications: from citizen service chatbots and document automation to intelligence analysis and national security applications. However, government adoption faces unique challenges around security, compliance, and data sovereignty that commercial AI solutions often cannot address.
Key Challenges for Government AI Adoption
A 2025 GAO report found that officials at 10 of 12 federal agencies identified existing policies as major obstacles to deploying AI for government applications:
- Data Privacy Policies: Existing federal data privacy requirements conflict with cloud-based AI
- Security Classification: Highly segmented data separated by classification levels
- Technical Resources: Insufficient infrastructure for secure AI deployment
- Commercial AI Limitations: Most AI solutions designed for commercial use cannot meet federal security requirements
- Data Sovereignty: Concerns about data leaving controlled environments
Generative AI in Government: Open-Source Models, Air-Gapped Deployment
Why the model you can hold beats the model you can only call
Generative AI in government grew faster than any other category of federal technology adoption in the last reporting cycle: the U.S. Government Accountability Office (GAO) recorded a ninefold increase in generative AI use between 2023 and 2024, inside a total inventory that nearly doubled from 571 to 1,110 use cases. Drafting, summarization, translation, and knowledge search account for most of that growth, and all four touch records an agency cannot hand to a third party.
That is the split that decides architecture. A hosted generative model is reached through an API, which means the prompt, the retrieved documents, and the output all cross an agency boundary. An open-weight model — one whose weights are published and downloadable — can be brought inside the boundary instead, inspected, frozen at a known version, and run on hardware the agency already accredits.
What open-source models change for an agency
- The weights are an artifact you hold. An open-weight model is a file on accredited storage, version-pinned like any other approved software baseline, not a service that can change behavior between two identical prompts.
- The boundary stops moving. With inference local, the authorization boundary for the AI capability is the boundary the agency already holds, so the NIST 800-53 controls in place for the enclave carry over instead of being re-negotiated for a new external connection.
- Cost stops scaling with use. Per-token metering makes the budget a function of adoption. Locally hosted models move the cost to hardware the agency owns, which is how a program office can let an entire division use the capability without a mid-year funding problem.
- Disconnected operation is possible at all. A SCIF, a DoDIN enclave, a forward site, or a field vehicle on an intermittent link cannot depend on an API being reachable. Only a locally resident model works when the network is not there.
- Records stay auditable. Prompts, retrieved sources, and generated text remain inside agency logging, which is what makes a FOIA response, an inspector general request, or an internal review answerable after the fact.
How agencies deploy it
Iternal delivers generative AI in government as three layers an agency can accredit separately: an open-weight model running locally, a curated data layer built with Blockify so answers come from approved agency source material rather than model recall, and a client that works with no outbound connection at all. That client is AirgapAI, which runs on standard AI PCs and on server hardware inside the enclave.
The deployment questions that follow are practical rather than theoretical: which enclave, which classification level, which accreditation path. The reference architecture is set out in the guide to deploying an LLM on premise, the isolation model in what is air-gapped AI, and the federal authorization path on the FedRAMP AI page. Agencies sizing the accreditation and licensing trade-off before a pilot can model it with the air-gapped AI for government calculator.
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Secure Local AI & Offline AI
AI solutions that never leave your controlled environment
Why Government Needs Air-Gapped AI
Traditional cloud-based AI creates unacceptable risks for government operations. When classified data, citizen information, or sensitive agency operations are involved, secure local AI and offline AI deployments are essential.
A truly air-gapped AI solution must meet four critical criteria:
- Zero External Dependencies: No remote API calls, no cloud inference, no internet connection required
- Static Model Behavior: All inference occurs locally with inspectable, frozen model weights
- Local Context Processing: All data processing happens entirely within your controlled perimeter
- End-to-End Auditability: Every interaction fully traceable for compliance and security reviews
AirgapAI
100% local AI processing with zero data transmission. The only offline AI solution purpose-built for government classified environments.
Learn About AirgapAIAI for SCIFs & Classified Environments
Bringing AI capabilities to the most secure government facilities
AI for Classified Government Operations
For teams working inside SCIFs (Sensitive Compartmented Information Facilities) and DoDIN enclaves, even a single external connection can disqualify an AI tool from use. AI for classified government environments requires a fundamentally different approach.
Microsoft recently deployed the first-ever air-gapped GPT-4 model specifically for classified workloads - a major breakthrough that demonstrates the critical need for offline AI for government applications. However, government agencies need solutions they can deploy on their own infrastructure without dependence on any single vendor.
On-Premises & Air-Gapped Deployment Options
Iternal offers multiple deployment models for public sector AI to meet every security classification level:
- AWS GovCloud: FedRAMP High authorized environment for CUI and sensitive workloads
- On-Premises Deployment: Full installation within agency-controlled data centers
- Air-Gapped Installation: Complete network isolation for classified environments
- SCIF-Compatible: Purpose-built for operation in compartmented facilities
- IL5/IL6 Capable: Supporting Secret and Top Secret classification levels
Security & Compliance Standards
Our AI for government solutions are designed to meet the most stringent security requirements:
- FedRAMP High: Aligned with federal security authorization requirements
- NIST 800-53: Full control implementation for federal information systems
- NIST 800-171: CUI protection for defense contractors
- FIPS 140-3: Validated cryptographic modules for data protection
- Section 508: Full accessibility compliance for all outputs
- STIG Hardened: Security Technical Implementation Guide configurations
Agencies deciding where each dataset may physically reside can work through the requirements for sovereign AI and data residency before committing to a deployment model.
Government Sectors We Serve
Comprehensive public sector AI solutions for every level of government
Federal Agencies
Enterprise-scale AI for federal departments with FedRAMP compliance
Defense & Intelligence
Air-gapped AI for SCIFs, classified operations, and national security
State Government
Statewide AI standardization and citizen service automation
Local Government
Municipal AI for community engagement and operational efficiency
Transportation Agencies
AI for passenger communications, safety training, and operations
Public Health
HIPAA-compliant AI for health communications and emergency response
Public Sector AI Use Cases
Explore how AI for government transforms agency operations
Administrative Task Automation
AI-powered automation for routine government processes
RFP/RFI Automation
AI for government procurement document generation
Multi-Language Communications
AI translation for diverse citizen populations
Policy & Procedure Management
Centralized AI-managed policy documentation
Cross-Agency Information Sharing
Secure AI for inter-agency collaboration
Rapid Response Training
AI-generated training for emerging situations
Personalized Citizen Services
AI-tailored service instructions for each citizen
Automated Government Reporting
AI-generated reports for stakeholders and citizens
Program Management
End-to-end AI for government project delivery
The Public Sector AI Hub
Every government page in one place: use cases, programs, compliance, case studies and planning tools
Government use cases
- Administrative task automation
- Government RFP and RFI automation
- Multilingual citizen communications
- Policy and procedure management
- Cross-agency information sharing
- Just-in-time rapid response training
- Personalized citizen service instructions
- Internal and public reporting
- Program and product management
Programs and compliance
Why Choose Iternal for Public Sector AI
Enterprise-grade AI for government built for security and compliance
Frequently Asked Questions: AI for Government
Common questions about public sector AI and secure deployment
Can AI run in a completely air-gapped environment?
Yes. AirgapAI is specifically designed for offline AI deployment with zero external dependencies. All model inference, context processing, and content generation happens entirely within your controlled perimeter with no internet connection required. This makes it suitable for SCIFs, classified networks, and other air-gapped environments.
What classification levels does your AI support?
Our AI for government solutions support all classification levels from unclassified through Top Secret. We offer AWS GovCloud deployment for CUI/IL5, on-premises installation for agency-controlled environments, and fully air-gapped deployment for IL6 and compartmented facilities.
How does secure local AI differ from cloud AI?
Secure local AI processes all data on your own infrastructure without transmitting information to external servers. This eliminates risks of data exposure, meets data sovereignty requirements, and enables use with classified information. Cloud AI, by contrast, sends data to external servers for processing.
What FedRAMP authorization level do you support?
Our public sector AI platform is architected to meet FedRAMP High requirements with STIG-hardened configurations, FIPS 140-3 validated cryptography, and full NIST 800-53 control implementation. We support deployment in FedRAMP-authorized cloud environments or on-premises installations.
Can your AI be used inside a SCIF?
Yes. AirgapAI is purpose-built for AI for SCIFs and other compartmented facilities. With zero external network connections, local-only processing, and complete auditability, it meets the stringent requirements for operation in sensitive compartmented information facilities.
How is AI used in the public sector?
The most common uses are citizen-facing service and correspondence, document and forms processing, translation, records search across agency knowledge, training content, and analysis support. The U.S. Government Accountability Office (GAO) counted 1,110 reported federal AI use cases in 2024, up from 571 the year before. State and local agencies follow the same pattern at a smaller scale, usually starting with correspondence and records.
What is generative AI in government used for?
Drafting and summarization carry most of the workload: policy and procedure documents, public notices, grant and procurement paperwork, briefing material, translated citizen communications, and training scenarios. Because those tasks touch controlled or classified records, agencies increasingly run generative models on their own hardware with an open-weight model rather than sending the text to a hosted API.
How should state and local government agencies start with AI?
Start with one records-heavy workflow the agency already staffs, such as multilingual citizen communications or policy management, and run it on a deployment the agency controls so CJIS, StateRAMP and public-records obligations are satisfied from day one. The state and local view, including procurement paths and shared-service models, is on the AI for SLED page.
How is public sector AI different from commercial enterprise AI?
Four constraints change the design: data classification levels that cannot be mixed, federal control frameworks such as NIST 800-53 and NIST 800-171, Section 508 accessibility for every generated output, and public-records and audit obligations that require the prompt and its sources to be retrievable later. Commercial platforms typically satisfy none of the four without an on-premise or air-gapped deployment.
Do government agencies have to use open-source AI models?
No, but open-weight models are what make a fully disconnected deployment possible. The weights can be downloaded, inspected, version-pinned and run inside an existing authorization boundary, so the capability inherits the controls the enclave already holds instead of requiring a new external connection to be accredited.
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