Guide · Architecture choice
EnclavAI vs ChatGPT FedRAMP / ChatGPT Gov / Azure OpenAI
OpenAI now offers multiple government paths — managed FedRAMP SaaS, self-hosted ChatGPT Gov on Azure, and Azure OpenAI Service across IL4–IL6. EnclavAI is a different lane entirely: local inference inside your boundary. They are complementary, not interchangeable.
OpenAI's government paths (quick map)
OpenAI is not one product for regulated work — buyers usually mean one of these:
-
ChatGPT FedRAMP (ChatGPT Enterprise + API for
FedRAMP): OpenAI-managed SaaS at FedRAMP Moderate (as of 2026), API via
gov.api.openai.com. Direct procurement for civilian agencies at the Moderate baseline — not a substitute for every CUI or DoD enclave without your AO's sign-off. - ChatGPT Gov: Containerized app you deploy in your Azure commercial or Azure Government tenant on top of Azure OpenAI Service. Designed for higher-control frameworks (IL5, CJIS, ITAR, FedRAMP High) when you operate the environment.
- Azure OpenAI Service (without the ChatGPT Gov shell): Microsoft's authorized path — FedRAMP High and DoD IL4/5/6 in Azure Government and classified regions. Many defense programs already standardize here before adding a ChatGPT-style frontend.
Can I use ChatGPT with CUI?
Commercial ChatGPT / api.openai.com: No for CUI — data leaves your assessment boundary onto commercial infrastructure not authorized for that processing.
ChatGPT FedRAMP (Moderate): Authorized for FedRAMP Moderate workloads when procured and operated per the package — useful for many civilian agency programs. Defense contractors handling CUI under CMMC/DFARS often need a documented enclave at IL4/5 or stricter; do not assume Moderate SaaS covers your contract without SSP review.
ChatGPT Gov / Azure OpenAI (Gov): Yes when configured inside an authorized Azure enclave — you inherit Microsoft/OpenAI controls for the tier you deploy (IL4, IL5, IL6 per Microsoft's authorization story). Your team still scopes CUI correctly, documents the system in your SSP, and operates within your CMMC boundary.
EnclavAI: Yes for teams that need the model inside their own boundary without any OpenAI or Azure API call — local open-weight inference (Ollama), zero egress by design, human approve/reject on every artifact, deterministic destructive-command gating, and tamper-evident signed evidence export.
Side-by-side (STIG / POA&M / DevSecOps focus)
| Dimension | OpenAI / Azure (authorized cloud) | EnclavAI (in-boundary local) |
|---|---|---|
| Where inference runs | OpenAI-managed (FedRAMP SaaS) or your Azure Gov / commercial tenant (ChatGPT Gov, Azure OpenAI) | Your VM, GovCloud EC2, Azure Gov VM, or air-gapped host — Docker Compose |
| Model | GPT-4o / o-series and successors (frontier, managed by OpenAI/Microsoft) | Open-weight local model (e.g. Qwen2.5-Coder 7B) — you control the artifact |
| Data egress | Prompts/responses traverse authorized cloud paths (must be in scope for your AO) | App + optional network-layer egress lock; no cloud LLM calls |
| Procurement path | FedRAMP marketplace (SaaS), Azure Government EA/CSP, or agency ATO on self-hosted ChatGPT Gov | Self-hosted product license / pilot — no OpenAI API dependency |
| Architecture pattern | Agents SDK, Assistants, or custom API apps — you design guardrails and logging | Sequential governed loop: ingest → draft → Evidence & Risk Scan → human approve → audit export |
| STIG remediation | Custom build on Azure OpenAI / ChatGPT Gov + your tools & guardrails | Built-in STIG agent, destructive scanner, .ckl round-trip, batch remediation UI |
| Evidence for assessors | You design logging, retention, and export (Azure Monitor, your app, OpenAI enterprise logs) | HMAC-signed evidence packages, per-artifact audit, offline verify script |
| Best when | You already standardized on Azure Gov + OpenAI; want frontier model; cloud enclave is approved | Air-gap, strict zero-egress policy, on-prem metal, or “no vendor LLM API” requirement |
| Partnership | OpenAI + Microsoft ecosystem (SI implementers, Azure Marketplace) | Self-hosted product — no OpenAI dependency |
Which should we choose?
Use this decision tree — many organizations use both in different enclaves:
- Choose ChatGPT FedRAMP if you are a civilian agency (or contractor supporting one) with an AO-approved Moderate baseline and want managed SaaS without operating Azure yourself.
- Choose ChatGPT Gov / Azure OpenAI if your security team has approved Azure Government (IL4/5/6 as required) for CUI in a documented enclave, you want frontier-model quality, and your cloud team can implement tools, logging, and SSP documentation.
- Choose EnclavAI if policy or contract language requires no external LLM API, you need air-gap or hard zero-egress, you want STIG/POA&M/SSP agents and C3PAO-style evidence out of the box, or you're a sub without an Azure OpenAI landing zone yet.
- Start with neither's production path — score your checklist first with the free in-browser STIG scorer (nothing uploads): enclavai.io/tools/stig-scorer.
How this relates to OpenAI's agent guidance
OpenAI's Agents documentation emphasizes explicit tool use, guardrails, and human oversight for high-stakes workflows — not unconstrained autonomous loops. EnclavAI applies that discipline with a local model: sequential draft → Evidence & Risk Scan → human gate → signed export. Different runtime than ChatGPT Gov; same instinct that compliance work needs control, not autonomy theater.
See also
Evaluating Anthropic instead? EnclavAI vs Claude Gov / AWS Bedrock — same complementary framing for the AWS/Anthropic path.
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