Brine/Solutions/Defense & Government

Your prime asked for your AI controls.
Your contracting officer is next.

Brine is the AI governance and execution platform for the defense industrial base. Built for CMMC L2, NIST 800-171, and DFARS 252.204-7021. Cryptographic identity per AI agent. SHA-256 audit trails. Assessor-ready evidence in minutes, not weeks.

Scope a pilot→See the platform →
How Brine fits the DIB

The governed layer between AI
and the mission.

Brine sits between the AI models your team runs and the environment they operate inside. Sovereign by default, model-neutral by design, operationally ready.

Operational readiness

A governed pilot live in minutes, not a nine-month program of record. Start on a non-regulated workflow, prove the numbers, expand.

Mission assurance

Every agent carries its own cryptographic identity. Every action is signed, attributable, and non-repudiable. Nothing unreviewed reaches production.

Enterprise modernization

Consolidate manual, high-volume work like evidence collection, vendor-risk intake, and screening under one governed execution layer.

Sovereign by default

Your keys or ours. Your models or ours. VPC-isolated. Architected to keep data inside your accreditation boundary.

The gap in your environment

Your prime is asking about your AI controls.
You do not have an answer.

The platforms your team runs on were built for humans only, with no identity, scope, or audit layer for AI systems. The compliance frameworks are catching up faster than the platforms.

01

Identity inherited

AI runs under human credentials. No cryptographic identity per system, no way to revoke a misbehaving agent without disabling a cleared person, no signed attribution when your assessor asks who acted.

02

Audit trails muddled

Actions get logged. They are not signed, not scoped to an agent identity, and not exportable as an immutable chain. When CMMC requires evidence of access control and audit, the platform has none to produce.

03

Accountability unclear

When a workflow produces a wrong answer, no chain of custody traces the decision back to a specific agent, model version, or scoped intent.

04

Cost invisible

AI spend gets reconciled after the contract period closes, not enforced before dispatch. No platform-level gate stops an agent from exceeding its allowance against your contract margins.

The consequence

When your contracting officer asks who approved a decision and your platform cannot distinguish human from AI, that is a CMMC finding, a contract risk, and a competitive liability on the next bid.

What we’d build for you

Workflows that run.
On data your team already handles.

Five examples of how a Brine pilot starts. Begin with how we’d scope a workflow with you, then page through four governed workflows we deploy on non-CUI data.

brine.ai / pilot / scope-a-workflowStart here

How we scope a workflow with you

Phase 0 · ~5 days from pilot signed to first agent live
Scoping
  1. AWorkflow inventory: list workflows in priority order
    client async · 5-question form
    ~5 min
  2. BPer-workflow intake: steps, inputs, approval gates
    client async · one form per workflow
    ~15 min ea
  3. CInternal scoping: map agents, gates, outputs to a visual
    Brine async · we draft, you confirm
    ~30 min
  4. DKickoff call: confirm the visual, lock Phase 1 dates
    both teams · 30-min call
    30 min
  5. EPhase 1 starts: first governed agent live
    joint · from kickoff
    ~10 days
Total client time pre-kickoff ~40 minFor the first workflow · +15 min each additionalBrine’s the rest
defense-sub.brine / workflow / cmmc-l2-evidenceActive

CMMC L2 Evidence Collection

Run cmmc4q26 · 4/5 steps complete · started 10:14 AM
Active
  1. APull NIST 800-171 control catalog
    agent action · scout
    4.8s
  2. BIdentify control owners + evidence sources
    agent action · resolver
    19.6s
  3. CCollect existing artifacts from SharePoint/Confluence
    agent action · evidence_collector
    47.3s
  4. DMap evidence to controls with citations
    agent action · audit_assistant
    1m 22.4s
  5. EGenerate self-assessment narrative
    agent action · narrative_author
    2.1s…
Run total $24.80110 controls scanned · 28 LLM callsEst. complete in ~2 min
defense-sub.brine / workflow / prime-flowdown-responseActive

Prime Flowdown Letter Response

Run pfd6c8b · 3/5 steps complete · started 9:42 AM
Active
  1. AParse flowdown letter from prime (Boeing/RTX/LM)
    agent action · parser
    6.3s
  2. BMap questions to internal controls + policies
    agent action · resolver
    22.1s
  3. CPull supporting artifacts per question
    agent action · evidence_collector
    38.6s
  4. DDraft attestation narrative per question
    agent action · narrative_author
    0:48…
  5. ERoute to compliance officer for review
    agent action · routing_assistant
    —
Run total $8.4014 questions answered · 11 LLM callsEst. complete in ~3 min
defense-sub.brine / workflow / subcontractor-riskComplete

Subcontractor Vendor Risk Intake

Run sub3vrk · 5/5 steps complete · non-CUI scope
Complete
  1. AIntake new subcontractor questionnaire
    agent action · intake_assistant
    5.8s
  2. BPull SAM.gov registration + CAGE code
    agent action · scout
    22.1s
  3. CScore against subcontractor risk matrix
    agent action · risk_analyst
    28.4s
  4. DQC, verify cited sources
    quality check
    11.2s
  5. EUpdate subcontractor risk register + notify owner
    agent action · register_assistant
    7.6s
Run total $2.80312k in · 19.4k out · 9 LLM callsProjected $4.52 · −38% vs. baseline
defense-sub.brine / workflow / sprs-affirmationComplete

Annual SPRS Affirmation Narrative

Run sprs5k7 · 5/5 steps complete · internal evidence only
Complete
  1. APull last cycle’s SPRS score + delta
    agent action · data_collector
    8.4s
  2. BCalculate control implementation status
    agent action · analyst
    14.2s
  3. CDraft annual affirmation narrative
    agent action · narrative_author
    1m 18.7s
  4. DCite evidence artifacts per control
    agent action · annotator
    10.4s
  5. EFormat for SPRS submission
    agent action · formatter
    9.5s
Run total $5.10110 NIST 800-171 controls covered~7 min vs. 6+ hours human prep

Brine does not touch CUI during pilot. Every workflow above runs on corporate-operations data: control catalogs, public registrations, internal evidence artifacts. Regulated-data scope expands after pilot.

Proof, not promises

Three workstreams, under full audit, for 90 days.

DoD subcontractor · Talent acquisition · Staffing

87%

Cycle-time reduction across high-volume resume screening.

A staffing firm processing high-volume resume screening for enterprise clients in the defense supply chain ran three concurrent workstreams under full audit for 90 days on Brine. Every AI action signed, scoped, logged, and costed to its own identity.

Per-batch screening time
120 min → < 15 min
Per-resume cost
$67 → < $0.01
Concurrent workstreams
3
Unreviewed AI actions in production
0
Live in minutes, not months

You don’t have nine months.
We get it done in minutes.

Most AI governance platforms run a nine-month sales cycle ending in a six-figure dashboard. Brine goes live in minutes on a non-CUI workflow your team runs today, and produces a working audit trail your contracting officer can see in thirty.

  1. 01

    Scope a workflow

    Pick a non-CUI workflow your team runs today. Corporate operations, vendor management, internal compliance documentation, anything repeatable.

  2. 02

    Live in minutes

    Brine deploys, governs, and runs the workflow inside your tenant. You measure cycle time, cost, and accuracy against your baseline.

  3. 03

    Expand on results

    Convert to production. Add scope. Bring CUI into the mix once the model is proven.

Your tenant. Your keys. Your data.180-day contractual transition path. On-premise deployment available.
Scope a pilot→See the platform →
Not in defense or government?