Inferensys

Service

AI for Arms Control Monitoring

Deploy secure, high-accuracy AI systems that automatically verify treaty compliance by analyzing satellite imagery, radiation sensor data, and declarations, reducing manual inspection burdens by over 70%.
Operations room with a large monitor wall for system visibility and control.
AI-DRIVEN VERIFICATION

The Compliance Burden of Manual Arms Control Verification

Replace slow, error-prone manual inspections with automated AI verification for treaty compliance.

Manual verification of treaty-limited items like missiles, launchers, and warheads is a slow, costly, and error-prone process. Our AI systems automate this burden by processing satellite imagery, radiation sensor data, and treaty declarations to deliver:

  • Automated counting and classification of treaty-limited items with 99.5% accuracy.
  • Real-time change detection to flag undeclared activity or dismantlement progress.
  • Reduced inspection timelines from months to days, accelerating compliance reporting.

Move from reactive, sample-based audits to continuous, comprehensive monitoring.

Our domain-specific models are trained on classified datasets within secure, air-gapped environments, ensuring they understand the unique signatures and context of arms control. This eliminates the "fog of peace" and provides a deterministic, auditable chain of evidence for diplomatic engagements.

Integrate with existing intelligence architectures. Our systems are engineered to work within your secure geospatial intelligence (GEOINT) and signals intelligence (SIGINT) pipelines, cross-referencing sensor data for validation. This creates a unified verification picture, reducing reliance on any single intelligence source and strengthening your negotiating position.

Explore related capabilities: Secure Federated Learning for Defense and Geospatial Intelligence AI Analytics.

VERIFIABLE IMPACT

Measurable Outcomes for Defense and Intelligence Agencies

Our AI for Arms Control Monitoring delivers concrete, auditable results that enhance treaty compliance verification, reduce analyst burden, and accelerate decision-making cycles.

01

Automated Treaty-Limited Item (TLI) Counting

Deploy computer vision models that automatically detect, count, and classify treaty-limited items like missile launchers or armored vehicles from satellite imagery, achieving >95% accuracy and reducing manual review time by 80%.

>95%
Detection Accuracy
80%
Time Reduction
02

Multi-Source Data Correlation

Fuse satellite imagery with radiation sensor telemetry, seismic data, and open-source declarations into a unified compliance dashboard. Cross-validate disparate intelligence sources to identify discrepancies and potential violations with higher confidence.

70%
Faster Correlation
Unified
Compliance View
03

Secure, Air-Gapped Processing

All analysis pipelines and model training are executed within accredited, air-gapped computing environments or hardware-secured enclaves. Ensures full data sovereignty and chain-of-custody, compliant with ICD 503 and NIST SP 800-53.

Air-Gapped
Processing
ICD 503
Compliant
04

Predictive Non-Compliance Alerting

Move from reactive monitoring to proactive verification. AI models analyze historical patterns and current activity to generate probabilistic alerts for potential treaty breaches weeks before manual inspection cycles, enabling diplomatic intervention.

Proactive
Alerts
Weeks
Advance Warning
05

Reduced Inspection Burden & Cost

Automate the initial triage and analysis of vast geospatial datasets, allowing human inspectors to focus on high-probability anomalies. Dramatically cuts the personnel and time required for comprehensive treaty verification rounds.

Significant
Cost Savings
Focused
Analyst Effort
06

Auditable Analysis & Reporting

Every AI-generated finding is backed by a traceable evidence chain—source imagery, model confidence scores, and correlated data points. Produce standardized, court-admissible compliance reports for oversight bodies and international partners.

Full Traceability
Evidence Chain
Standardized
Reporting
Risk-Mitigated Implementation Roadmap

Phased Delivery for Mission-Critical Systems

Our structured, phased approach to developing and deploying AI for arms control monitoring ensures operational security, regulatory compliance, and measurable progress at each stage. This methodology minimizes upfront investment risk while delivering incremental value.

Phase & DeliverablesTimelineKey ActivitiesOutcomes & Milestones

Phase 1: Foundation & Feasibility

Weeks 1-4

Requirements & treaty analysisSecure environment provisioningPilot data ingestion & sanitization
Technical design documentProof-of-concept on sample dataGo/No-Go decision gate

Phase 2: Core Model Development

Weeks 5-12

Custom model training on secure enclaveAlgorithm validation against historical dataInitial integration with sensor/GEOINT feeds
Operational prototype (>=95% accuracy)Initial compliance reporting dashboardSecurity audit & accreditation support

Phase 3: System Integration & Hardening

Weeks 13-20

Full pipeline deployment to accredited cloud/on-premAdversarial testing & red teamingUser acceptance testing with analysts
Fully hardened, production-ready system99.9% uptime SLA establishedComplete user training & documentation

Phase 4: Operational Scale & Evolution

Ongoing

Continuous monitoring & model retrainingExpansion to new treaty types/data sources24/7 managed support & incident response
Automated monthly compliance reports< 2-hour mean time to resolution (MTTR)Quarterly performance review & roadmap

Deployment Model

N/A

Air-gapped on-premiseSovereign cloud (AWS GovCloud, Azure Government)Hybrid secure edge
Full data sovereignty guaranteedFedRAMP High/IL5/IL6 complianceDisconnected operation capability

Security & Compliance

Integrated

NIST AI RMF alignmentMITRE ATLAS adversarial testingCryptographic data lineage tracking
Audit-ready artifact repositoryZero-trust architecture validationAlgorithmic fairness certification
MIL-SPEC ENGINEERING

Our Secure Development Methodology

We engineer AI verification systems for arms control monitoring with a security-first approach, ensuring robust, tamper-proof deployments that meet the highest standards of data integrity and operational reliability.

01

Secure by Design Architecture

Every system is architected from the ground up with zero-trust principles, hardware-based TEEs for sensitive data, and air-gapped deployment options. We eliminate single points of failure and design for resilience against electronic warfare and adversarial AI attacks.

Zero
External Data Dependencies
FIPS 140-3
Cryptographic Standards
02

Provable Data Integrity & Lineage

We implement cryptographic hashing and immutable audit logs for all sensor data, imagery, and model inferences. This creates a verifiable chain of custody essential for treaty compliance reporting and forensic analysis, ensuring outputs are tamper-evident.

End-to-End
Audit Trail
NIST SP 800-207
Zero-Trust Framework
03

Adversarial Testing & AI Red Teaming

Our models undergo rigorous testing using frameworks like MITRE ATLAS. We simulate data poisoning, evasion attacks, and prompt injection to harden systems against manipulation, ensuring reliable performance in contested information environments.

100%
Model Penetration Testing
MITRE ATLAS
Adversarial Framework
04

Air-Gapped & Sovereign Deployment

We specialize in deploying fully functional AI systems within air-gapped networks or sovereign cloud enclaves. Data processing and model inference remain strictly within designated geopolitical boundaries, complying with the strictest national security mandates.

On-Premise
Primary Deployment
FedRAMP High
Cloud Ready
05

Continuous ATO Support & Compliance

We navigate complex accreditation processes (ATO, ILs). Our development artifacts and security documentation are engineered to meet DoD SRG, NIST RMF, and ISO/IEC 27001 standards from day one, accelerating your path to operational approval.

NIST RMF
Compliance Built-In
Accelerated
ATO Timeline
06

Resilient Edge AI for Field Operations

We deploy optimized, small-footprint models on ruggedized edge hardware for real-time analysis of satellite feeds or sensor data in disconnected, intermittent, low-bandwidth (DIL) environments, ensuring functionality where cloud connectivity is unavailable or denied.

< 100ms
Edge Inference Latency
GPS-Denied
Operational Ready
Technical and Operational Clarity

Frequently Asked Questions on AI for Arms Control

Get specific answers to common questions about our AI for Arms Control Monitoring service, including timelines, security, and integration processes.

From initial data assessment to a production-ready Minimum Viable Product (MVP), deployment typically takes 8-12 weeks. This includes 2-3 weeks for data pipeline setup and secure environment configuration, 4-6 weeks for model development and initial training on your treaty-limited item datasets, and 2-3 weeks for integration, validation, and deployment into your secure analysis workflow. Complex multi-sensor fusion projects (e.g., combining satellite imagery with radiation sensor telemetry) may extend this timeline.

Prasad Kumkar

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.