Enterprise AI Platforms for Government Agencies
Government enterprise AI platforms consolidate AI infrastructure across agency initiatives: shared model serving (FedRAMP-eligible or sovereign), retrieval infrastructure, evaluation pipelines, governance frameworks aligned with NIST AI RMF and OMB guidance, audit logging that satisfies OIG / IG / GAO review, accessibility compliance for any public-facing components. BearPlex builds these platforms with the rigor public sector requires from day one.
Why Enterprise Platform Engineering matters in Government & Public Sector
Government agencies are increasing AI investment but per-project infrastructure isn't sustainable. Every government AI initiative needs FedRAMP-eligible deployment, accessibility compliance, audit logging, civil rights / disparate impact analysis where relevant, NIST AI RMF integration, sector-specific compliance. Building per-project across many initiatives is wasteful and produces inconsistent compliance that fails examiner review. Platform approach is more efficient and more defensible. The platforms that work in government are designed by engineers who understand both the technology and the regulatory / public-sector procurement realities.
Typical enterprise platform engineering use cases in government & public sector
| Application | Description | Timeline | Tech stack |
|---|---|---|---|
| FedRAMP-eligible model serving infrastructure | Shared model serving on FedRAMP-authorized cloud (AWS GovCloud, Azure Government): managed AI where authorized, self-hosted open-source for sensitive workloads. | 16-24 weeks | AWS Bedrock GovCloud · Self-hosted vLLM in GovCloud · Identity federation with agency systems |
| Centralized AI governance framework | Governance framework aligned with NIST AI RMF and OMB M-24-10: model registry, validation evidence, ongoing monitoring, and OIG audit support. | 20-28 weeks | Model registry infrastructure · Audit logging to immutable storage · Validation framework |
| Disparate impact analysis platform | Civil rights and disparate impact analysis infrastructure for AI in consequential decisions: benefits, employment, housing, credit, criminal justice. | 16-22 weeks | Statistical analysis frameworks · Demographic data integration · Compliance documentation |
| Accessibility-aware developer experience | Internal SDK that bakes accessibility (Section 508, WCAG 2.2 AA), FedRAMP compliance, audit logging, and AI governance into every AI feature by default. | 14-20 weeks | Custom internal SDK · Accessibility component library · Compliance abstractions |
| Sovereign AI deployment infrastructure | For agencies requiring sovereign deployment beyond GovCloud: on-prem GPU clusters, air-gapped infrastructure, classified-environment-eligible deployment patterns. | 20-28 weeks | On-prem vLLM · Kubernetes on-prem · Air-gapped operation patterns |
What we've learned deploying enterprise platform engineering in government & public sector
Three patterns from BearPlex government enterprise AI platform engagements: (1) FedRAMP authorization shapes everything; platform deployment must satisfy FedRAMP requirements per the agency's sensitivity level (Moderate, High, IL5/6); (2) Accessibility is non-negotiable for any public-facing component: Section 508 + WCAG 2.2 AA from day one rather than retrofitting; (3) Procurement and contracting timelines exceed engineering: federal platform engagements often take 12-24 months end-to-end from initial conversation to fully operational platform.
Government & Public Sector compliance considerations
Government enterprise AI platforms must meet: FedRAMP authorization (Moderate / High / IL5/6 per sensitivity); NIST AI Risk Management Framework; OMB M-24-10 and follow-on AI guidance; civil rights / disparate impact requirements for consequential decisions; sector-specific frameworks; Section 508 / WCAG accessibility for public-facing components; FOIA / Privacy Act / FISMA for data and records. State / local equivalents apply for non-federal engagements.
Common questions
Yes: for higher-sensitivity workloads, we use AWS GovCloud or Azure Government IL5/6 environments. Most managed AI services don't have FedRAMP High authorization, so we typically use self-hosted open-source models.
Designed for it. The platform's governance framework satisfies OMB M-24-10 expectations: AI use case inventory, risk management, transparency, performance monitoring, redress mechanisms. Documentation supports agency CIO submission requirements.
Yes: required for AI affecting consequential citizen decisions. The platform includes infrastructure for measuring model performance across protected demographic groups, identifying disparate impact patterns, and documenting analysis for civil rights review.
$600K-$2M+ for the initial 16-24 week engagement that stands up platform foundations. Ongoing development typically requires 4-8 dedicated engineers. Procurement and contracting timelines separate.
Yes: common engagement type. State and local government platform requirements parallel federal but with state-specific frameworks (StateRAMP, state-specific accessibility / public records laws).
We support CUI workloads in appropriate environments (GovCloud, IL5/6). For classified workloads (Secret, Top Secret), we partner with prime contractors who have appropriate clearances.
This service in other industries
Other services for Government
Featured case studies
Ready to deploy enterprise platform engineering in government & public sector?
Start with a paid Discovery Sprint. We'll scope the engagement, validate compliance fit, and quote a fixed price.