Get your AI through FedRAMP authorization without losing the budget cycle.

Yes, but the AI itself is rarely the boundary. What gets authorized is the system that hosts and uses the AI: your application, the inference endpoints, the data pipelines, the logging, and the human review workflows. The model weights and the LLM provider are treated as a service component within that boundary. The right architecture choice (self-hosted open weights, FedRAMP-authorized LLM provider, or a hybrid) depends on your impact level, your data sensitivity, and how much control you need over prompts and outputs.

The list changes constantly, so always verify on the FedRAMP Marketplace before architecting around a specific provider. As of early 2026, several major commercial LLM providers have FedRAMP Moderate or High authorizations either directly or through hyperscaler GovCloud environments (AWS GovCloud, Azure Government, Google Cloud for Government). For agencies that need full data isolation, self-hosting open-weight models inside your authorized boundary remains the safest path.

If your existing ATO boundary already covers compute and data services that can host the AI workload, a Significant Change Request with appropriate continuous monitoring updates is typically the fastest path, measured in weeks to a few months, not the 12-18 months a fresh authorization takes. The variable is how much your AI changes data flows, system boundaries, or risk posture. We help you scope that change up front so you do not discover scope creep mid-review.

Impact level is driven by the data the system handles, not the AI itself. Moderate covers most non-classified federal data including controlled unclassified information (CUI). High is required for systems where loss of confidentiality, integrity, or availability would have a severe or catastrophic effect, typically law enforcement, emergency services, financial systems, and certain health data. AI inference, training data handling, and prompt logging all need to be designed for the impact level you are targeting.

Yes. FedRAMP gives you a security baseline. The NIST AI Risk Management Framework (AI RMF), OMB Memorandum M-24-10, and any agency-specific AI directives sit on top of that baseline and govern how the AI is used, monitored, and held accountable. We help agencies map AI RMF controls to their existing FedRAMP control inheritance so they are not maintaining two parallel compliance programs.

Yes. Most of our federal work flows through prime contractors. We can sit on the prime’s paper, follow their security plan, and coordinate with their existing FedRAMP package. Bring us in early. The cheapest time to fix an AI architecture decision is before the SAR is written.

Three differences. First, we ship code. We are not a slide deck and a roadmap. Second, every engagement is led by senior engineers with 25+ years of enterprise IT and direct compliance experience, not pyramid-staffed with junior consultants. Third, we have shipped Human-AI products in production ourselves, so we know where AI breaks under real federal constraints. If you need a 200-page deliverable, we are not your firm. If you need an authorized, working system, we are.