PLAYBOOK · GOVERNMENT & DEFENSE
Air-gapped document classification and triage.
In defense and sovereign government settings, no document leaves the perimeter — yet classification, redaction, and routing still need to happen at speed. This playbook composes on-prem SLMs, intent templates, and human-in-the-loop review into one auditable network.
The problem
Sovereignty is non-negotiable
Defense and government workloads cannot ship documents to public clouds. Yet classification queues are massive, and human throughput alone is insufficient. The right balance is automation that augments — never replaces — the cleared reviewer.
The VDF AI approach
Local models, strict policies, transparent runs
VDF AI runs entirely on customer hardware, supports local SLMs, and exposes every routing decision. Domain-level policy enforces who can see which document and which model can process it.
REFERENCE ARCHITECTURE
Documents move, not data
OCR · metadata extraction
Local SLM
Domain rules · marking conventions
Domain-scoped policy
PLAYBOOK · STEP BY STEP
Stand up an air-gapped triage line
Deploy VDF AI fully on-prem
Air-gapped, customer-hosted SLMs, no mandatory cloud dependency. Use VDF AI Compliance to define the security envelope.
OCR and metadata extraction
Use the built-in ocr MCP tool plus custom extractors to normalize scanned and digital documents.
Author classification and redaction agents
Each agent uses a tight, deterministic system prompt and outputs structured JSON: marking, confidence, justification.
Enforce domain policy
Domains scope which agents and models can see which document. AgentsHub enforces role-based access at routing time.
Human-in-the-loop review
Low-confidence cases route to cleared reviewers. Every model decision is replayable.
OUTCOMES
Throughput up, sovereignty intact
data leaves the perimeter — air-gapped by design.
throughput on routine classifications.
decisions replayable for inspector general or audit reviews.
SEEMR REFERENCE
Routing inside the boundary
SEEMR's energy and capability modes are doubly valuable when every model runs locally. SEEMR matches model size to task difficulty without leaving the network.
GET IN TOUCH
You Have Questions
Tell us what you’re trying to achieve—governed AI Networks, enterprise RAG, deep integrations, or on‑premise deployment. We’ll help you map the right architecture, security posture, and rollout path. If you’re moving beyond AI pilots and need scalable, auditable execution, reach out—our team is ready to help.