AI governance binders, risk documentation, audit materials, and a laptop showing an AI review workflow.

AI governance that holds up in federal work.

Five Scoops helps federal-facing teams turn US government AI expectations into practical policies, controls, review records, and evidence packages.

Federal AI use Governance roles, inventories, risk reviews, and public trust expectations.
AI acquisition Procurement language, vendor evidence, and contract-ready documentation.
NIST-aligned controls Govern, Map, Measure, and Manage practices translated into operating routines.

Compliance support for teams using, buying, or selling AI in government settings.

Government AI work is moving from broad principles into operational requirements: who owns the system, what risks were reviewed, what data and model limitations are known, how outputs are monitored, and what evidence can be produced when a reviewer asks.

Five Scoops focuses on that translation layer. The work is plain-language, documentation-heavy, and designed for people who need to show their reasoning without burying the team in theory.

The pieces that make AI governance reviewable.

AI use inventory

Identify AI systems, classify use cases, define owners, and capture the minimum facts needed for governance, review, and reporting.

Policies and controls

Create review procedures, acceptable-use rules, human oversight steps, control narratives, and escalation paths that teams can operate.

Procurement support

Prepare AI governance responses, vendor questionnaires, contract inputs, and evidence packets for federal acquisition conversations.

Executive briefing

Turn technical and legal detail into board-ready, officer-ready, or proposal-ready material that explains risk, decisions, and next steps.

Built around current US government AI expectations.

The site draft is intentionally specific, but not overpromising: this practice supports compliance documentation and governance operations, not legal advice.

01

OMB M-25-21 AI governance and public trust

Governance roles, AI maturity, risk management, inventories, and public trust practices reflected in current OMB AI-use guidance.

02

OMB M-25-22 AI acquisition and contractor readiness

Documentation patterns for planned acquisitions, vendor review, performance and risk management practices, and contract-facing AI evidence.

03

NIST AI RMF and generative AI risk

Practical mapping to Govern, Map, Measure, and Manage, including generative AI risks, monitoring, limitations, and user-facing controls.

04

Evidence, monitoring, and human oversight

Operating language for accuracy, uncertainty, limitations, human review, and post-deployment monitoring where AI affects important decisions.

A focused path from uncertainty to usable governance materials.

1

Baseline

Review current AI uses, proposal needs, policies, customer obligations, and existing evidence.

2

Map

Connect the work to federal AI guidance, acquisition requirements, NIST practices, and team ownership.

3

Build

Draft policies, control language, review templates, risk records, questionnaire responses, and briefing content.

4

Handoff

Package the material so it can be updated, reused, and defended by the team after the engagement.

Best for lean teams that need senior compliance thinking without a heavy consulting machine.

  • Federal contractors adding AI governance to proposals, security packages, or customer reviews.
  • Product and operations teams that need clear AI review routines before a procurement or audit.
  • Executives who need plain-language material on AI risk, controls, and compliance posture.
  • Organizations preparing to explain how AI is governed, monitored, and documented.

Tell me what needs to stand up to review.

Share the AI system, policy question, customer request, proposal need, or documentation gap. The form uses a simple bot check and opens an email addressed to ambar@fivescoops.com.