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Agile Release Trains inside federal civilian agencies. AI inside state operations. Constituent-facing services rebuilt on modern Agile cadences. NIST RMF, FedRAMP, and FISMA literacy is baseline here, not a learning curve.
Government AI consulting is the work of designing, building, governing, and authorizing AI systems inside federal, state, and local agencies under the rules that actually govern public IT. That means the NIST AI Risk Management Framework (AI 100-1), FedRAMP (Low, Moderate, High), FISMA, OMB M-24-10, EO 14110, the FAR / DFARS clauses tied to the contract vehicle, CMMC for defense-adjacent work, Section 508 accessibility, and the OMB Circulars (A-130, A-11) that govern federal IT investments. The unit of measure is not a TechCrunch demo. It is time-to-ATO, cATO continuous monitoring posture, and constituent outcomes inside accessible, audit-defensible systems. Rockmere runs that work inside federal civilian programs, state IT shops, and local service-delivery organizations.
The NIST AI RMF (AI 100-1) is a voluntary federal framework that organizes AI risk management into four functions: Govern, Map, Measure, and Manage. We stand up all four as artifacts alongside the technical build, not as a compliance afterthought.
Most government Agile transformations stall at the SDLC. Teams adopt Scrum, the dashboards go up, security review takes 14 weeks, and the iteration cadence becomes theatre. The fix is not more training. It is redesigning how authorization, NIST AI RMF compliance, and Agile delivery move at the same speed.
You accelerate an Authorization to Operate (ATO) by producing the security artifacts inside the delivery cadence instead of after it. Time-to-ATO is the lever that moves everything else. We design the SDLC so the System Security Plan, Security Assessment Report, POA&M, and control implementations are byproducts of the iteration cycle, not a nine-month post-build workstream. Typical impact: a 30% to 50% reduction in time-from-code-complete to authorized-to-operate. The biggest gains come from cATO (continuous ATO) patterns and continuous monitoring readiness, not from paperwork tricks.
For AI systems we stand up the NIST AI RMF Govern, Map, Measure, and Manage functions alongside the technical build. Risk classification, impact assessment, performance characterization, human-in-the-loop boundaries, and continuous monitoring instrumentation are part of the design package. OMB M-24-10 minimum practices for safety-impacting and rights-impacting AI shape the human-oversight pattern from day one. The retrieval and citation discipline often runs through our enterprise RAG consulting practice when the AI grounds answers in policy, statute, or regulation. Section 508 accessibility is baked into the interface before the first usability test, not retrofitted before the public-facing release.
The contract vehicle constrains the engagement shape before the work even starts. We have worked under GSA Multiple Award Schedule (MAS), GWAC vehicles, agency-specific IDIQs, 8(a) sole-source awards, SBIR Phase II contracts, and state contract schedules. We have sub-contracted under prime contractors, prime’d ourselves on smaller awards, and supported BPA holders. We are not currently a GSA Schedule holder ourselves, and we hold Public Trust and Secret clearances on the team but no facility clearance (FCL) as a firm. For FCL-required environments we sub-contract under cleared primes. We say so upfront because the alternative wastes everyone’s procurement cycle.
FAR / DFARS clauses, CMMC certification expectations, OMB M-24-10 compliance, and EO 14110 implementation requirements shape every government AI consulting build we stand up. FISMA Moderate and FedRAMP Moderate / High boundaries inform the architecture before the first commit. We design with the contracting officer’s representative and the agency CIO’s office in the room from week one. When the procurement requires a small-business set-aside, an HUBZone partner, or a service-disabled-veteran-owned (SDVOSB) partner, we name the partner before the proposal is filed rather than after the award lands.
Government AI consulting at Rockmere usually pairs three services on the engagement:
Federal civilian agencies adopt SAFe® at the program level around major investment portfolios. State governments adopt SAFe® across agency IT shops. Local governments rarely need full SAFe®. Essential SAFe® or team-level Agile is usually the right fit. We diagnose which level fits in the first two weeks rather than installing the full framework reflexively. The SAFe® SPCT credentials behind those engagements are re-verified quarterly on the credentials page.
One concrete example of AI in government: a state Medicaid program cut benefits-eligibility disposition time by 42% with a decision-support AI, while completing its full NIST AI RMF risk assessment package in parallel with the build. The program needed faster dispositions without weakening the audit posture. The system was designed for cATO continuous monitoring from day one. The full write-up is in the State Medicaid Eligibility AI case study. HIPAA overlap with our healthcare AI consulting practice was material on that engagement.
By the end of a government AI consulting engagement you have:
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