In classified networks, traditional perimeter security fails. Adversaries with privileged access can exfiltrate model weights, training data, and sensitive inferences. Our TEE-based AI development ensures data and algorithms are cryptographically sealed within hardware enclaves like
Intel SGXandAMD SEV, even if the host OS is breached.
Service
TEE-Based AI for Defense and Intelligence
Development of air-gapped, hardware-rooted AI systems for classified data processing, ensuring model integrity and preventing data exfiltration even on compromised infrastructure within secure government networks.
TEE-BASED AI FOR DEFENSE AND INTELLIGENCE
The Challenge: Securing AI in High-Threat Environments
Deploy hardware-rooted, air-gapped AI systems that protect classified data and model integrity on potentially compromised infrastructure.
- Hardware-Rooted Trust: Deploy AI models within attested
Trusted Execution Environments (TEEs). Code and data integrity is verified via remote attestation before any computation begins. - Zero-Trust Data Processing: Sensitive data is decrypted, processed by the AI model, and re-encrypted solely within the secure enclave's memory. It is never exposed to the cloud hypervisor, host OS, or other tenants.
- Prevent Model Theft & Tampering: Protect proprietary algorithms and fine-tuned weights from insider threats and infrastructure-level attacks, ensuring model integrity throughout its lifecycle.
We architect end-to-end confidential AI pipelines for defense applications, from secure data ingestion to air-gapped inference. This enables:
- Processing of Top Secret/SCI-level intelligence data on shared cloud infrastructure.
- Secure multi-party computation for joint analysis between allied agencies without raw data exchange.
- Deployment of autonomous systems where algorithmic integrity is non-negotiable, even in disconnected, intermittent, or low-bandwidth (DIL) environments.
Move beyond vulnerable software stacks. Our expertise in confidential computing for AI workloads delivers provably secure systems that meet the strictest defense and intelligence mandates. Explore our broader approach to securing sensitive data in use or learn about secure multi-party AI computation services for collaborative analysis.
SECURE, AIR-GAPPED AI
Operational Outcomes for Defense & Intelligence
Deploy hardware-rooted AI systems that process classified data with guaranteed integrity, preventing exfiltration even on compromised infrastructure. Our TEE-based solutions deliver mission-critical reliability and compliance.
01
Hardware-Rooted Data Integrity
AI models and sensitive data are cryptographically sealed within Intel SGX or AMD SEV enclaves. This ensures model integrity and prevents tampering or data exfiltration, even if the host operating system or hypervisor is compromised. Critical for processing Top Secret/SCI materials.
Zero Trust
Data-in-Use Protection
FIPS 140-3
Cryptographic Validation
02
Air-Gapped Inference Enclaves
Deploy isolated, attestable AI inference endpoints within secure government networks (e.g., JWICS, SIPRNet). Models operate in memory-encrypted enclaves with no persistent external network access, meeting the strictest air-gap requirements for classified processing.
Guaranteed
Network Isolation
Remote Attestation
Enclave Verification
03
Secure Multi-Party Intelligence Fusion
Enable joint analysis across agencies without sharing raw data. Our secure multi-party computation services, built on TEEs, allow models to be trained and infer on combined datasets from CIA, DIA, and NSA sources while preserving each agency's data sovereignty.
Data Sovereignty
Per-Agency Control
Secure Aggregation
Federated Learning
05
Compliant AI for IC Directives
Architectures designed to comply with Intelligence Community Directive (ICD) 503, CNSSI 1253, and the Zero Trust Reference Architecture. We implement policy-as-code and continuous monitoring to maintain accreditation for systems processing classified data.
ICD 503
Security Compliance
Continuous ATO
Monitoring
06
Resilient Edge AI for Contested Environments
Deploy lightweight TEEs on tactical edge devices for local inference on sensor data (RFML, video). Enables AI-powered decision support in disconnected, intermittent, and limited (DIL) environments without risking data spillage via satellite backhaul.
DIL Environment
Operational Readiness
On-Device
Encrypted Inference
Risk-Mitigated Implementation
Phased Delivery for Controlled Deployment
Our structured approach to deploying TEE-based AI systems ensures security validation and operational readiness at each stage, minimizing risk for sensitive defense and intelligence applications.
| Deployment Phase | Core Objectives | Key Deliverables | Timeline | Security Validation |
|---|---|---|---|---|
Phase 1: Architecture & Attestation | Define secure data flow, select TEE hardware (Intel SGX/AMD SEV), establish remote attestation chain. | Threat model, attested environment design, cryptographic key management plan. | 2-3 weeks | Initial attestation protocol validation against MITRE ATLAS. |
Phase 2: Enclave Prototyping | Develop minimal viable enclave for core AI inference, integrate with secure boot and measured launch. | Functional prototype, encrypted model loading pipeline, performance baseline. | 3-4 weeks | Memory integrity verification, side-channel resistance assessment. |
Phase 3: Pipeline Integration | Integrate enclave into existing classified data pipeline (air-gapped networks), implement secure I/O. | End-to-end encrypted data pipeline, integration test suite, operational runbook. | 4-6 weeks | Full data-in-use protection audit, penetration testing on I/O channels. |
Phase 4: Staged Rollout & Monitoring | Deploy to non-critical subsystem, monitor for stability and performance under load, gather operational telemetry. | Deployment to staging environment, performance & security dashboard, incident response playbook. | 2-3 weeks | Continuous attestation monitoring, anomaly detection for exfiltration attempts. |
Phase 5: Full Operational Capability (FOC) | Certify system for production use on classified networks, transition to ongoing support and maintenance. | Final accreditation documentation, SLA agreement, handover to operational team. | 1-2 weeks | Final security accreditation (e.g., FedRAMP High equivalency), compliance sign-off. |
Ongoing: Security Posture Management | Continuous monitoring, attestation, and updates to address novel threats and maintain air-gap integrity. | Monthly security reports, vulnerability patches, attestation log review. | Continuous | Integration with enterprise AI-SPM and Shadow AI Detection platforms. |
HARDWARE-ROOTED SECURITY
Secure AI Applications for National Security
Deploy AI systems that process classified data with guaranteed integrity. Our TEE-based solutions prevent data exfiltration and model tampering, even on compromised infrastructure, meeting the strictest defense and intelligence requirements.
01
Air-Gapped AI Model Deployment
Deploy and run sensitive AI models in hardware-isolated enclaves (Intel SGX, AMD SEV) with no external network connectivity. Ensures model weights and inference data are cryptographically sealed from the host OS, hypervisor, and cloud provider personnel.
Learn more about our approach to Confidential AI Inference Enclave Development.
Zero-trust
Network Model
Hardware-rooted
Attestation
02
Secure Multi-Agency Intelligence Fusion
Enable joint analysis across different intelligence agencies using secure multi-party computation within TEEs. Agencies can contribute encrypted data for combined AI analysis without exposing raw, classified sources to each other, breaking down data silos securely.
This architecture is powered by our Secure Multi-Party AI Computation Services.
Data Sovereignty
Maintained
Aggregated Insights
Shared Output
03
Tamper-Evident Model Integrity
Implement continuous remote attestation to cryptographically verify that your AI model is executing unaltered within a genuine TEE. Any attempt to modify the model, runtime, or underlying platform is immediately detected, preventing supply chain attacks and insider threats.
Real-time
Attestation
Cryptographic Proof
of Integrity
04
Encrypted Geospatial & SIGINT Analytics
Process satellite imagery, signals intelligence (SIGINT), and other sensitive geospatial data within secure enclaves. AI models for object detection and pattern analysis run on encrypted data, ensuring raw intelligence never persists in plaintext in memory or storage.
Explore our capabilities in Geospatial AI and Spatial Analytics (GeoAI).
In-memory Encryption
Data Protection
Classified Data
In-Use Security
05
Confidential Edge AI for Field Operations
Deploy lightweight TEEs on tactical edge devices for real-time sensor (video, RF, biometric) analysis. Perform AI inference locally without transmitting raw data, enabling immediate decision-making in disconnected, intermittent, or low-bandwidth (DIL) environments while preserving operational security.
On-Device
Processing
No Data Egress
Required
06
Compliant AI for Classified Networks
Architect systems that meet specific government directives (e.g., JADC2, IC directives) and regulatory frameworks for AI in national security. Our TEE integration provides the technical controls for data-in-use protection mandated by evolving defense cybersecurity policies.
Directive Alignment
Built-in
Audit-ready
Architecture
AIR-GAPPED, HARDWARE-ROOTED SECURITY
TEE-Based AI for Defense and Intelligence
Deploy air-gapped, hardware-rooted AI systems for classified data processing, ensuring model integrity and preventing data exfiltration.
Our methodology builds AI systems where sensitive data and model weights never leave the secure memory enclave. We architect solutions using hardware-based Trusted Execution Environments (TEEs) like Intel SGX and AMD SEV to create an immutable, hardware-rooted chain of trust, even on potentially compromised infrastructure.
This transforms your secure network from a passive container into an active, intelligent asset capable of processing classified data with zero trust in the underlying host OS or cloud provider.
- Guaranteed Data-in-Use Protection: AI inference and training occur within cryptographically isolated memory enclaves, preventing exfiltration of model IP or sensitive intelligence data.
- Hardware Attestation & Integrity Verification: Every enclave is cryptographically measured and attested before execution, ensuring the AI workload runs only on authorized, unaltered hardware and software stacks.
- Air-Gapped Operational Design: We engineer systems for deployment in classified, disconnected environments, with secure data ingestion and output protocols that maintain the integrity of the air gap.
- Compliance-Built Architecture: Designs inherently satisfy mandates like NIST SP 800-171 and CMMC for controlled unclassified information (CUI) and align with frameworks like MITRE ATLAS for adversarial ML defense.
Enabling Efficiency, Speed & Accuracy
Intelligent Analysis, Decision & Execution
We build AI systems for teams that need search across company data, workflow automation across tools, or AI features inside products and internal software.
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Search across company data
Give teams answers from docs, tickets, runbooks, and product data with sources and permissions.
Useful when people spend too long searching or get different answers from different systems.
Enterprise searchRAGPermissions
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Automate internal workflows
Use AI to route work, draft outputs, trigger actions, and keep approvals and logs in place.
Useful when repetitive work moves across multiple tools and teams.
AI agentsWorkflow automationGovernance
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Add AI to products and internal tools
Build assistants, guided actions, or decision support into the software your team or customers already use.
Useful when AI needs to be part of the product, not a separate tool.
AI integrationDecision supportModel routing
Read moreFor Defense and Intelligence Applications
Frequently Asked Questions on TEE-Based AI
Get clear, specific answers about deploying hardware-secured AI systems for classified environments. Based on our experience delivering air-gapped, hardware-rooted solutions for secure government networks.
Standard deployments for a hardened, air-gapped AI system take 4-6 weeks from architecture sign-off to operational readiness. This includes hardware provisioning, secure OS configuration, model integration into enclaves (e.g., Intel SGX, AMD SEV), and attestation pipeline setup. Complex multi-party computation or cross-domain solutions can extend to 8-12 weeks. We provide a fixed-scope project plan with weekly milestones.
About the author
Prasad Kumkar
CEO & MD, Inference Systems
Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.
His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.
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How We Work
Custom AI workflows for your Business
One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
01
Review the use case
We understand the task, the users, and where AI can actually help.
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Pick the right approach
We define what needs search, automation, or product integration.
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Build the first useful version
We implement the part that proves the value first.
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Improve from there
We add the checks and visibility needed to keep it useful.
Read moreThe first call is a practical review of your use case and the right next step.
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