The productivity of generative AI — for proposals, past performance, and program data that can't touch a public cloud.
DPLYD puts a fully managed AI appliance inside your perimeter. Controlled Unclassified Information stays on your network — and so does every index, embedding, and log derived from it.
DPLYD for defense is a managed on-premises AI appliance for contractors handling CUI: BD search, proposal drafting, and program knowledge retrieval run entirely inside your boundary, aligned with your CMMC 2.0 Level 2 posture.
NIST 800-171's data-flow controls — 3.1.x access enforcement, 3.13.x boundary protection — exist to keep CUI inside a defined, assessed enclave. Every cloud AI tool asks you to ship that same CUI to a server outside it.
That's not a convenience question. It's a scope question. If the assessment boundary doesn't cover the AI vendor's cloud, the CUI shouldn't be reaching it — full stop.
You built your compliance posture around a defined enclave. That instinct was right. AI shouldn't be the exception that punches a hole in it.
Most "on-prem-friendly" defense AI keeps the document local — then ships an index of it to the cloud. That distinction is marketing, not a control boundary.
An index derived from your proposal file is a second copy of the sensitive part:
Verbatim passages lifted straight out of a proposal or program document. Not a summary. The text itself.
Encode the meaning, and are reversible enough to reconstruct the source.
Program names, teaming partners, contract numbers, proposal themes — in plaintext.
Authors, dates, solicitation numbers, file paths: a map of every program you're pursuing.
Which teaming partners, primes, and programs connect. Disclosure without a single sentence leaving.
The original file never moved. The CUI did.
A cloud index of local CUI is outside the boundary the moment it can disclose, infer, search, or reconstruct protected material off your enclave. DPLYD keeps the index on the same side of the boundary as the file. Always.
DPLYD is a managed AI appliance that lives inside your assessed boundary. The model runs where your program data already is.
CUI never crosses your enclave. Full generative capability, zero egress of controlled data.
We own the hardware, updates, and lifecycle. Your team operates; we maintain. No new servers for your IT to babysit.
Fixed monthly. No per-seat licensing. No per-token metering. No capex. Every BD, capture, and proposal staffer works from the same appliance — price doesn't climb because you gave the whole team access.
DPLYD isn't a narrow point-tool. The appliance runs capable general models — the same drafting, summarizing, and reasoning your team would reach for anywhere — plus program-specific workflows on top.
One appliance serves the whole capture and delivery organization. Program work gets program handling; everything else your people do with AI runs on the same secure box.
Compliance shouldn't be a slide deck you assemble the week before a C3PAO assessment. DPLYD produces an immutable, exportable record of every AI interaction: what ran, on which documents, under what policy, with what result.
When an assessor asks for evidence — or when a program audit surfaces two years later — the record already exists.
| GovCloud SaaS AI | DPLYD | |
|---|---|---|
| Where the model runs | Vendor's FedRAMP/GovCloud tenancy | Inside your facility |
| Where the index lives | Vendor cloud, outside your enclave | Same side of the boundary as the data |
| ATO / assessment surface | A new external system to scope and trust | An asset inside your existing boundary |
| Evidence at assessment | Vendor attestations and contract language | Immutable, exportable record on demand |
| Pricing | Per-seat / per-token, scales with usage | Fixed monthly — no per-seat, no per-token |
| Disconnected / air-gapped work | Not possible — requires connectivity | Supported by design |
GovCloud SaaS AI is still someone else's cloud — inside the FedRAMP boundary, but outside yours. DPLYD refuses that trade: the intelligence comes to the data.
Some work simply cannot go to a third-party API: CUI under NIST 800-171, programs preparing for CMMC 2.0 Level 2 assessment, export-controlled technical data, and any contractor that treats its assessment boundary as non-negotiable.
If your answer to "where does the data go?" has to be nowhere outside the enclave — DPLYD is the only version of this that works.
Deploy generative AI on 20 years of BD content without violating CMMC Level 2 posture or exposing controlled data to frontier models.
Read the case study →Yes, if the entire processing chain stays inside your assessed boundary. That is the design constraint DPLYD is built around: model, index, embeddings, and logs all remain on your network.
The appliance is deployed inside your existing boundary and inherits your enclave's controls; Sentinel produces the audit evidence assessors ask for. It is scoped as an asset within the boundary, not a new external service.
Most "compliant" AI tools keep the file local but ship an index to their cloud. An index is derived CUI. DPLYD keeps the index on the same side of the boundary as the data.
The appliance can run fully disconnected. Managed updates are delivered on a schedule and mechanism that fits your environment, including offline transfer for air-gapped enclaves.
A 30-minute walkthrough of the appliance, running on your data, inside your boundary.