Government agencies are under pressure to adopt AI quickly. But public-sector requirements — data sovereignty, auditability, procurement rules, and security controls — make the consumer and SaaS playbook a poor fit.
The agencies that adopt AI well will be the ones that evaluate vendors on the right criteria. Here's the checklist worth holding every AI vendor to.
1. Can it run sovereign and air-gapped?
The first test is deployment. Can the platform run on-premise, in GovCloud, and in a fully air-gapped environment with no external connectivity?
Many AI products offer "on-premise" that still phones home for model serving or licensing. For classified and IL5 workloads, that's disqualifying. True sovereignty means zero external dependencies after deployment.
2. Do you own the code and the data?
Procurement should ask whether the agency receives the source code or merely licenses access. Ownership — via a full code license — is what enables source-level security review, long-term continuity, and freedom from vendor lock-in.
Data must stay inside the agency's perimeter, with every interaction logged for IG investigations and FOIA compliance.
3. Does it meet the control frameworks?
NIST 800-53 alignment, FedRAMP pathways, PIV/CAC authentication, and complete audit trails should be table stakes. The question is whether these are properties of the architecture or promises in a contract. Owned, self-hosted systems make them demonstrable.
4. Is it model-agnostic?
Agencies shouldn't bet a multi-year program on one vendor's models. A model-agnostic platform lets an agency run private open models for sensitive workloads and switch as capabilities and approvals evolve — without re-procuring the platform.
This is a structural advantage over both the consumer "Gov" editions of frontier models and single-model enterprise vendors.
5. Who owns and operates the vendor?
For government and defense, the vendor's own profile matters. ibl.ai is family-owned and operated from New York, NY — a domestically-owned, independent, long-term partner, not a foreign-owned or venture-controlled company optimizing for its next raise.
That independence and continuity are exactly what multi-year public programs need.
6. Will the agency build capability, not dependency?
The best engagements transfer capability. ibl.ai's forward-deployed engineers deploy the platform in the agency's environment, integrate it with existing systems, and hand operational ownership to agency staff — so the agency owns the system after knowledge transfer.
The takeaway
Government AI procurement should test for sovereignty, ownership, control, model freedom, and a stable domestic partner — not just model quality. See the government solution, the self-hosted AI hub, and the ChatGPT Gov alternative for how ibl.ai meets the checklist.