Deploy AI with authorized cloud services for government agencies and contractors. Our service delivers a fully compliant environment—from initial security control mapping to final authorization support—enabling you to focus on mission-critical AI applications.
Service
FedRAMP-Compliant AI Infrastructure
Engineering AI hosting environments that meet the stringent U.S. Federal Risk and Authorization Management Program (FedRAMP) security controls, enabling government agencies and contractors to deploy AI with authorized cloud services.
Engineer AI hosting environments that meet stringent U.S. Federal Risk and Authorization Management Program (FedRAMP) security controls.
We architect the secure foundation so you can deploy AI with confidence, meeting federal mandates without sacrificing innovation speed.
- Control Implementation: Map and implement the ~325 FedRAMP Moderate or ~421 High security controls for your AI stack, including data encryption, access logging, and continuous monitoring.
- Infrastructure as Code: Deploy compliant environments using
TerraformandAnsiblewith auditable, repeatable configurations forAWS GovCloud,Azure Government, or on-premises stacks. - Continuous Compliance: Integrate automated scanning and reporting tools to maintain an always-audit-ready posture, reducing manual overhead by 70%.
- Accelerated ATO: Leverage our pre-built
Security Packagetemplates and expertise to shorten your Authority to Operate (ATO) timeline by 40%.
This service is part of our broader Sovereign AI Infrastructure Development pillar, which also includes Air-Gapped AI System Deployment for the highest security assurance and EU AI Act Compliant AI Development for European mandates.
GUARANTEED SECURITY AND EFFICIENCY
Business Outcomes of a FedRAMP-Compliant AI Platform
Achieve mission-critical AI deployment with a platform engineered to meet the highest U.S. federal security standards, delivering tangible operational and strategic advantages.
01
Accelerated Authority to Operate (ATO)
Leverage our pre-built, continuously audited infrastructure to reduce your FedRAMP authorization timeline from 12-18 months to under 6 months. Our platform includes pre-configured security controls, documented evidence packages, and integration with accredited FedRAMP 3PAOs.
< 6 months
Avg. ATO Timeline
100%
Control Inheritance
02
Uninterrupted Mission Continuity
Deploy AI with a 99.9% uptime SLA backed by geographically redundant, U.S.-based data centers. Our infrastructure ensures high availability for critical applications, with automated failover and continuous monitoring to meet Federal Continuity of Operations (COOP) requirements.
99.9%
Uptime SLA
< 15 min
Recovery Time Objective
04
Predictable, Compliant Cost Structure
Transition from unpredictable cloud spend to a fixed-cost, FedRAMP-authorized environment. Our platform includes built-in FinOps tools for AI workload optimization, eliminating the cost and complexity of securing and monitoring a DIY compliant cloud.
40-60%
Lower TCO vs DIY
$0
3PAO Re-audit Fees
Risk-Mitigated Implementation
Phased Delivery for FedRAMP Authorization
Our structured, multi-phase approach to building FedRAMP-compliant AI infrastructure reduces technical and compliance risk, accelerates the authorization timeline, and ensures continuous value delivery.
| Phase & Deliverables | Timeline | Key Outcomes | Authorization Progress |
|---|---|---|---|
Phase 1: Security Control Gap Analysis & Architecture Blueprint | 2-3 weeks | Comprehensive FedRAMP control mapping, technical architecture design, and prioritized remediation roadmap. | Foundational documentation for System Security Plan (SSP). |
Phase 2: Core Infrastructure & Technical Control Implementation | 4-6 weeks | Deployment of secure, air-gapped compute environment; implementation of logging, monitoring, and encryption controls per NIST 800-53. | Ready for 3PAO pre-assessment; 60% of technical controls validated. |
Phase 3: Continuous Monitoring & Policy Automation | Ongoing | Operationalization of continuous monitoring tools, automated compliance checks, and security incident response playbooks. | Full operational capability (FOC); supports ongoing assessment for Authority to Operate (ATO). |
Total Time to Operational Readiness | 6-9 weeks | Fully functional, compliant AI hosting environment ready for model deployment and security assessment. | Accelerates path to Provisional Authorization to Operate (P-ATO) by 40-60%. |
Compared to In-House Build | 6-12+ months | Eliminates unguided control implementation, reduces rework, and provides expert-led compliance narrative. | High risk of failed assessment or major findings without experienced FedRAMP partner. |
SECURE, CERTIFIED, AND PROVEN
Designed for Government and Defense AI Applications
Our FedRAMP-compliant infrastructure is engineered to meet the stringent security and operational demands of U.S. federal agencies, defense contractors, and intelligence communities, enabling secure AI deployment at scale.
01
FedRAMP Moderate & High Authorizations
We engineer and operate AI environments that meet all FedRAMP security controls. Our systems are designed for authorization, with continuous monitoring and audit-ready documentation to support your agency's ATO process.
800+
Security Controls
Continuous
Compliance Monitoring
02
Air-Gapped & Physically Isolated Deployments
For the most sensitive workloads, we design and deploy fully isolated AI training and inference clusters with no external network connectivity, preventing data exfiltration and ensuring the highest security assurance. Learn more about our Air-Gapped AI System Deployment methodology.
Zero Trust
Network Architecture
On-Prem
Deployment Option
03
Sovereign Data Residency & Jurisdictional Control
Guarantee that all training data, model weights, and inference outputs are processed and stored exclusively within U.S. borders. We implement technical controls and provable audit trails for full data lineage and residency assurance, aligning with mandates for Sovereign AI Data Residency Assurance.
100%
U.S. Data Processing
FIPS 140-3
Validated Cryptography
04
Hardware Segmentation & Supply Chain Integrity
We provision and manage dedicated AI accelerators (GPUs, NPUs) and compute clusters that are physically reserved for your entity. This ensures performance isolation, prevents resource contention, and mitigates supply chain risks through vetted procurement.
Dedicated
Compute Silos
US-Based
Hardware Sourcing
05
Continuous Monitoring & AI-Specific Threat Detection
Our infrastructure includes AI-native security monitoring that goes beyond traditional IT. We implement frameworks like MITRE ATLAS to detect and respond to novel AI threats, including model manipulation and data poisoning, as part of our AI Red Teaming and Adversarial Defense services.
24/7/365
SOC Oversight
MITRE ATLAS
Threat Framework
06
Compliant MLOps & Sovereign Lifecycle Management
Operate a complete, sovereign machine learning lifecycle within your controlled environment. Our platform enables secure model development, versioning, CI/CD, and monitoring without reliance on external, non-compliant SaaS tools, ensuring end-to-end governance.
Full Audit Trail
Model Lineage
On-Prem
Toolchain
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
Read more
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
Read more
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 Government Agencies and Contractors
FedRAMP AI Infrastructure: Frequently Asked Questions
Get clear, specific answers to the most common questions about deploying AI in environments that meet U.S. federal security standards.
For a standard deployment, the typical timeline is 2-4 weeks from kickoff to initial operational capability. This includes environment provisioning, security control implementation, and initial model deployment. Complex integrations with legacy government systems can extend this to 6-8 weeks. Our fixed-scope methodology ensures predictable delivery.
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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