The foundation
NVIDIA describes its Blueprints as reference solutions — flexible starting points that developers adapt and extend into production. That downstream role is Enclave's entire product: the Blueprint is the retrieval engine, and Enclave is the governed application built on top of it. Enclave tracks upstream Blueprint releases, so every deployment inherits NVIDIA's ongoing investment in ingestion, retrieval, and inference.
The stack
Enclave runs as four hardened services above the NVIDIA stack. Everything below the Enclave layer is standard NVIDIA software, deployed as NVIDIA ships it.
The orchestration
Out of the box, the Blueprint runs the same five steps on every question — one fixed pipeline, one shot, stateless. Excellent retrieval, and single-purpose by design:
Enclave's LangGraph orchestrator does not replace that pipeline — it makes it one of several specialists. A supervisor routes each turn with a structured decision; specialists do the work and report back; the supervisor looks at what has been gathered and routes again — up to six hops, under wall-clock and search budgets — before composing the answer. The Blueprint's round trip is what the rag specialist calls:
And because the loop runs inside the platform, governance is woven through every hop — the retrieval filter is built server-side from the asker's permissions before the engine is ever called, and the whole turn lands in the audit log:
The division of labor
The NVIDIA RAG Blueprint is deliberately decomposable — a modular reference architecture, not a finished enterprise application. Its own documentation describes the included interface as a sample, not a production surface. That is by design: the application layer is where independent software vendors are meant to build. This table is the honest split.
| Capability | NVIDIA RAG Blueprint | Enclave adds |
|---|---|---|
| Ingestion | Multimodal extraction — text, tables, charts, images | Upload lifecycle, per-corpus collections, connector-driven sync with deletion reconciliation, chunking tuned per corpus |
| Retrieval | Hybrid vector search with reranking | Permission-aware scoping per user and group, enforced server-side on every query; multi-collection strategy under budgets |
| Generation | Accelerated inference with citations | Agent orchestration (routing, multi-step tool use, sandboxed analysis), answer verification, streaming reasoning trail |
| Identity | — | OIDC single sign-on, role- and group-based access control, group sync from the identity provider |
| Interface | Sample interface for evaluation | Production chat application (white-label), projects/workspaces, admin console |
| Governance | Optional guardrails | Append-only audit trail with per-turn permission scope, usage accounting, guardrail profiles, prompt-injection defense |
| Quality | — | Scored evaluation harness, customer gold sets with negative controls, written acceptance criteria, quarterly quality reports |
| Operations | Docker Compose / Helm reference deploys | Hardened deployment profiles, mTLS between services, secrets management, backup/restore runbooks, managed-operations tier |
Why this matters to the ecosystem
Every NVIDIA-edition deployment requires an NVIDIA AI Enterprise subscription, licensed per GPU and resold with the engagement — recurring NVIDIA software revenue on hardware that would otherwise run an unsupported stack.
Enclave converts Blueprint evaluations into production deployments — the exact pilot-to-production step the Blueprint is designed to seed. We track upstream releases, so customers stay on current NVIDIA software.
Enclave serves the $30–250k deployment band: below the threshold where global systems integrators engage, above what an IT team can self-assemble from a repository. Coverage where the ecosystem is thinnest.
Public-sector and regulated buyers are Enclave's focus: environments governed by DFARS 252.204-7012 and NIST SP 800-171, no-cloud-AI policies, and disconnected networks — where a supported, fully on-premises stack is the requirement, not a preference.
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Provenance
Enclave's founder deployed the NVIDIA RAG Blueprint in production while building a U.S. state treasury's private AI platform — multi-agent retrieval over sensitive financial data, local models, enterprise SSO and role-based access — and rebuilt the application layer clean-room as the Enclave product. Enclave is a member of the NVIDIA Partner Network (Independent Software Vendor).
Next step
A live walkthrough of Enclave on NVIDIA hardware — sign-in to cited, permission-scoped answer — takes about fifteen minutes.
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