For federal customers, FedRAMP authorisation is the binding constraint on AI-for-security procurement. Google offers Gemini in FedRAMP-authorised environments through Google Public Sector; Anthropic's Claude is available through AWS GovCloud with FedRAMP-aligned deployment options. Either is a suitable underlying model for a FedRAMP-aligned security workflow. The comparison is not about the model — it is about what the customer team has to build on top.
What FedRAMP asks for
Four documentation categories:
- System Security Plan describing controls and their implementation.
- Continuous monitoring covering vulnerability posture and change management.
- Incident response commitments and evidence of exercise.
- Control-level evidence mapped to the applicable baseline (Low, Moderate, High).
Each applies to the entire system, not just the model layer.
What the model alone provides
Both Gemini (FedRAMP) and Claude (via GovCloud) provide:
- FedRAMP authorisation for the model infrastructure.
- Data handling documentation for the model layer.
- Platform-level SOC 2 and similar attestations.
This covers the foundation. The workflow layer is separate.
What Griffin AI adds on top
Five workflow-level FedRAMP-aligned artifacts:
- Workflow-specific SSP content. Griffin AI's contribution to the customer's SSP is documented.
- Continuous vulnerability monitoring with documented SLAs.
- Incident response commitments tied to the security workflow.
- Control-mapped evidence at the NIST 800-53 control level.
- FedRAMP-aligned data residency through on-prem and GovCloud deployment options.
For federal customers, this reduces the SSP content the customer team has to write from months of work to weeks of review.
A concrete procurement question
A federal customer asks: "If we build a security assistant directly on Gemini's FedRAMP deployment, what SSP content do we need to write ourselves?"
The answer is substantial. The model is FedRAMP; the workflow is not. Data flows, retention, access controls, audit logging — all have to be documented at the workflow level.
With Griffin AI on top: most of this content is pre-written. The customer reviews, adapts to their environment, and submits.
What to evaluate
Three questions:
- FedRAMP authorisation status of the deployment option being considered.
- How much of the SSP content is provided vs how much the customer writes.
- What evidence generation is automated vs manual.
How Safeguard Helps
Safeguard's FedRAMP readiness includes pre-written SSP content, automated continuous monitoring evidence, incident response commitments, and control-level mapping at the NIST 800-53 level. For federal customers whose FedRAMP ATO timeline is the binding constraint, this reduces Griffin AI adoption from "build a compliance package" to "review and submit."