AI/HPC Integration & Validation
Build Systems That Compute at Mission Speed
From large-scale simulations to mission-critical inference pipelines, CriticalTilt engineers and validates AI and high-performance computing environments that meet the real-world demands of federal agencies, national labs, and security-cleared research programs.
Whether your environment is air-gapped, hybrid, or fully on-prem, we help you build and operationalize advanced compute systems that are secure, scalable, and ready to perform under pressure.
AI/HPC That Meets Your Mission, Not Just the Spec Sheet
Our team supports agencies tasked with solving some of the hardest technical challenges in the world—under strict compliance, legacy constraints, and accelerating mission requirements. The stakes are high, and the margin for error is low.
We don’t just build for performance. We build for reproducibility, auditability, and deployment inside real-world infrastructure with real-world limitations. That’s why cleared agencies trust CriticalTilt to design and validate their most demanding systems.
We don’t need a learning curve. We’re already up to speed.
Problems We Solve
Your AI Stack Won’t Run Inside Your Clearance Zone
Most tools aren’t built for the constraints of secure or air-gapped systems. We engineer secure containers, support offline inference, and ensure every layer of the stack meets your policy.
Your Compute Throughput Doesn’t Match Model Needs
Too often, AI systems are deployed on general-purpose hardware or misconfigured clusters. We validate performance against live training and inference use cases to unlock full system potential.
You Can’t Trust Model Performance at Scale
A model that works in dev doesn’t always work in prod. We stress test under real data, simulate edge loads, and ensure determinism for high-sensitivity use cases.
What We Do
We offer end-to-end support across the full AI/HPC lifecycle—from initial architecture to live system validation.
Core Capabilities Include:
Architecting GPU-accelerated HPC clusters using NVIDIA, AMD, and custom compute nodes
Designing and deploying AI infrastructure inside TS/Q-cleared, air-gapped environments
Validating performance under production-scale stress and compliance conditions
Tuning and optimizing distributed compute and storage throughput
Integrating AI/ML workflows with hardened MLOps pipelines (Kubernetes, SLURM, Terraform)
Securing containers and model endpoints with NIST 800-53 and FIPS-aligned controls
Supporting hybrid environments with cloud-native orchestration for on-prem execution
Automating benchmarking, health checks, and reproducibility for model training
Why CriticalTilt
Most vendors focus on speed, scale, or security. We focus on all three—because we know your environment demands it.
DOD and DOE Cleared Engineers
We deploy directly into classified and compliance-sensitive environments—without handholding.
Mission-First Design
Our solutions don’t just compute fast—they work under your policy, bandwidth, and facility constraints.
Agile and Embedded
We partner like a boutique firm, deliver like a prime contractor, and document like a federal integrator.
Validation, Not Just Installation
Our process doesn’t stop at “deploy.” We validate end-to-end—ensuring models run right, at scale, the first time.
What We Deliver
Outcomes that actually move the needle.
Accelerated Go-Live
Reduce HPC system validation from months to weeks
Maximized Resource Use
Achieve up to 80% GPU/IO utilization under real workloads
Audit-Ready Compliance
Fully documented and hardened builds aligned with NIST and FedRAMP
Repeatable Deployments
Create system blueprints that scale across agencies or programs
Our work is built to withstand review—and outperform under pressure.
Who We Work With
We’re brought in when systems need to work—not just look good on paper.
Trusted By Our Clients
OEM and Tech Partners
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Let’s Build Together
If you’re planning or struggling with a secure AI or HPC deployment, we’re here to help. No fluff, no jargon—just a team of engineers who’ve done this before, and will do it again.