The determination
Name the decision, affected party, current case state, and downstream action.
Federal and public sector
Why was AI allowed to make or materially influence this federal determination?
A model explanation does not satisfy federal accountability by itself. The agency must be able to reconstruct the evidence, delegated authority, workflow state, human role, and mission consequence that justified AI’s participation in the decision.
Mission value with a durable decision record.Control must remain visible after the use case is approved.
Mission accountability
An explanation of the model is not an explanation of federal authority.
Models, people, evidence, vendors, policies, and systems may all contribute to the outcome. The organization still needs a clear view of who held authority and why the action proceeded.
The evidence and authority
Show what information supported the decision and what AI, the reviewer, and the program were permitted to do.
The operational record
Preserve why the action proceeded, was held, or moved to a different authority.
Policy context
Connect federal AI policy to the mission decision in front of you.
The official sources frame the conversation. The agency still has to define the mission outcome, accountable authority, operating evidence, acquisition choices, and path into production.
OMB M-25-21
Use the official memorandum as a policy anchor while defining the agency’s own mission decision, authority, evidence, and operating controls.
OMB M-25-22
Connect acquisition choices to the workflow, performance questions, ownership, and production consequences the agency must manage.
NIST AI RMF
Use a common risk-management reference while assigning agency-specific ownership, decisions, evidence, and production responsibility.
Acquisition and delivery
Begin with one regulated workflow and a bounded decision.
The initial work can map the decision state, evidence, authority, review, and consequence before any runtime control is introduced.
Mission workflow
Define the decision, outcome, authority, and operating constraint.
Acquisition evidence
Connect requirements and acceptance to realistic use.
Production validation
Test the complete workflow before scale.
Decision control
Preserve authority and the action record as conditions change.
Federal readiness
Prepared to support federal delivery.
GNS-AI maintains the following federal registration identifiers and Illinois certification.
SAM UEI
C1EYJ21KFCD3
CAGE Code
97ST4
Illinois BEP
Certified.
Teaming
GNS-AI works with certified small business partners holding federal contract vehicles, providing architecture, decision design, validation, and control.
Buyer questions
Questions federal leaders must be able to answer.
Mission use, acquisition, authority, and operational evidence belong in the same conversation.
How does GNS-AI approach federal AI work?
GNS-AI begins with the mission workflow, the decision authority, and the evidence that must survive review. The engagement can connect governance, acquisition, production validation, and runtime decision control while respecting agency environments, contractor roles, and existing delivery structures.
How can an agency connect M-25-21 and M-25-22 to a live workflow?
Begin with the agency’s own mission decision: what AI may influence, who remains accountable, what evidence must exist, and what happens before an action proceeds. M-25-21 and M-25-22 provide the policy context; agency counsel and responsible officials determine how they apply.
Can GNS-AI participate through a prime or contract-vehicle holder?
GNS-AI can work as a specialist decision-design, validation, architecture, or control workstream within an established delivery team. The team structure is confirmed for the specific opportunity.
Start a conversation
Discuss a federal workflow.
Bring the mission decision, acquisition question, pilot, or production workflow that must withstand review.
A useful first conversation: The first step is to identify the mission workflow, accountable owner, environment constraints, and the next decision gate.