A defensible path from AI idea to controlled implementation, with evidence at every step that a program office, a security reviewer, and a procurement lead can each read.
Brief status: Version 0.1 · 2026-09-05 · reviewed for claim safety
A federal program has AI in it already. A vendor added a model to a workflow, an analyst team is using an assistant, or a pilot proved useful and now wants a production path. Then the questions arrive from three directions at once. The program office needs an inventory and a risk classification that fits current OMB federal AI guidance. Security needs to know what data the model can reach, what tools it can call, and how an interaction is reconstructed after the fact. Procurement needs language it can defend in an acquisition.
Nobody on the program owns all three, and the guidance keeps moving. The result is a stalled use case or, worse, a deployed one with no decision record behind it. What the program needs is a defensible path from AI idea to controlled implementation, with evidence at every step that a reviewer can read.
The operating model below is how we structure a readiness and governance engagement. It is a reference design drawn from our own templates and from solution work in unawarded pursuits. It is not a description of an awarded contract.
Every AI use case on the program is recorded with owner, purpose, data classes, model source, deployment location, and human-oversight point. The register is the program's single artifact of record and stays with the program.
Each use case is tiered against the NIST AI RMF functions (Govern, Map, Measure, Manage) and screened for the high-impact criteria in the OMB memorandum in force at engagement start. Tiering is documented with the reasoning, not just the result.
For each use case we document where the model runs, where data travels, and which tools the model can invoke. The decision between a vendor-hosted service and a private or controlled deployment is written down with its trade-offs. This is the decision most programs skip and most reviewers ask about first.
Controls are mapped onto the baseline the program already runs, typically NIST SP 800-53 Rev. 5, with NIST SP 800-171 where controlled unclassified information is in scope. We document once and tag against each framework rather than building a second control set.
Each use case gets a defined test profile: what is measured, the threshold, the adversarial cases (prompt injection, data exposure, tool misuse), and who signs the result. We state that a model was tested against a defined profile. We never state that it is universally safe or compliant.
The output the program office, security, and procurement can each read: the register, the tiering record, the boundary memo, the control map, the evaluation profile and results, and a short readiness roadmap with owners and dates.
Scope. One program or one workflow, unclassified, with a named program owner. Larger scopes are sequenced as repeat engagements or as a build-after-award workstream.
Artifacts. AI use-case register; risk-tiering worksheet with rationale; boundary decision memo; control map onto the program's existing baseline; evaluation profile and first results; readiness roadmap; acceptable-use and model change-control templates adapted to the program.
Timeline band. Four to eight weeks for one program or workflow. Fixed scope and a written fee after a 30-minute scoping call; published pricing on the site governs.
How we work. Senior practitioners do the work directly. The register and templates are handed over in editable form so the program can maintain them without us.
If a program needs its AI inventoried, tiered, bounded, and evidenced before a reviewer asks, request a Federal AI Readiness briefing. We will return a written scope and fixed fee after one 30-minute call.