Factory Private
Federal Deployment
FedRAMP AI deployment without approval shortcuts
September 18, 2026 - 2 minute read
FedRAMP AI deployment requires an exact service description and current status. A product family, a cloud region, and an authorization claim describe different things. Combining them into a single approval assumption creates an avoidable procurement risk.
Start with the proposed workflow and the officials responsible for reviewing it. Identify the repository, execution environment, model service, integrations, and evidence that will support the decision.
FedRAMP AI deployment starts with the named offering
As of September 18, 2026, Factory FedRAMP describes control-plane and analytics hosting in GovCloud and states that authorization is in progress.
Preserve that qualification in an evaluation. Do not call the offering authorized or imply that hosting location completes the approval process. Obtain current status and scope before making a deployment commitment.
FedRAMP's initial agency authorization guidance provides a reference for the responsible agency reviewers. They should determine the applicable process for the proposed service and system.
Keep evidence dated. A vendor page can change, and an approval milestone may cover a narrower scope than the configuration a team wants to use.
Scope FedRAMP AI deployment across its dependencies
Request an offering-specific architecture. Confirm execution placement, supported model arrangements, session handling, telemetry destinations, and customer responsibilities. Avoid copying assumptions from a commercial deployment.
Factory's whitepaper distinguishes its managed, private, and federal offerings. Public descriptions differ on some federal execution details, so the agreed architecture should resolve those details before implementation.
Include supporting services in the review. Package repositories, scanners, identity systems, and ticketing integrations can create connections beyond the agent control plane. Record what each receives and which operator maintains it.
Give unresolved questions an owner and a resolution condition. A successful demonstration should not turn an unconfirmed feature or data path into an accepted production requirement.
Keep GovCloud and airgap decisions separate
A connected government-cloud service and a disconnected customer environment have different operating assumptions. Select the deployment against the workload's actual requirement.
Factory's airgap documentation describes a dedicated enterprise build that uses internal model endpoints and skips Factory-bound services. Cloud-dependent functions such as session sharing and hosted analytics are unavailable.
For that pattern, internal source control, packages, models, and evidence collection must support the whole task. A connected pilot does not validate the disconnected workflow.
Customer hosting also carries operating work. Assign responsibility for releases, certificates, model-service availability, incident handling, and recovery. Confirm which obligations remain with the customer before choosing the configuration.
Test the approved workflow, then preserve the record
Use a bounded task with data permitted for evaluation. Record its approved destinations, effective permissions, required tests, and review gate.
Factory's compliance guidance describes complementary audit and workflow evidence. Use the sources supported by the selected offering and confirm that reviewers can access them.
Exercise harmless failure cases alongside the successful task. Check that prohibited access is rejected, missing dependencies are visible, and the resulting change still requires the agreed approval.
Before expansion, reconfirm the service scope and status. Preserve the responsible authority's decision with the tested configuration. The final acceptance should describe the system that will run, not a broader product category.
