Targeting Judgment & Assurance
Machine-speed decision support across the targeting cycle — without ceding human command authority. Every recommendation is sourced, every law-of-war and ROE question is an explicit gate, and every judgment is logged, reversible, and defensible. Decision-Quality™ assurance, at the speed of command.
Guided demonstration · Exercise VANTAGE SHIELD
A notional joint force observes a pattern suggesting an adversary command-support function — sited near a protected facility. Press play, or step through it live in a brief. Every move is written to the audit ledger as it happens.
Stress the assurance model directly. Push civilian uncertainty or deception up and watch the gates close.
The recommendation the workbench would brief — and the gate it would hold.
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Adjust the sandbox to see how the verdict and gates respond.
Six capability facets
Facet 01
Turns a commander's guidance into a machine-checkable decision frame — while preserving ambiguity for human judgment. It separates what the AI can infer from what it cannot, and surfaces the questions command must answer before anything advances.
Facet 02
Shows how collection, source reliability, recency, contradictions, and assumptions support — or weaken — staff confidence. Every AI summary links back to evidence and uncertainty markers. No source, no score; no score, no advancement.
Facet 03
Converts law-of-war and ROE concerns into explicit gates requiring staff, legal, and command review — distinction, military necessity, proportionality, unnecessary suffering, protected objects, civilian-harm. The AI raises the question; it never makes the determination.
Facet 04
A built-in red team that turns the model against its own conclusions: alternative hypotheses, source-discipline checks, deception tests, and model-failure warnings. The system must try to disprove itself before it is allowed to brief confidence.
Facet 05
Captures every AI assertion, staff action, commander acceptance, legal note, model version, and override. The accountability trail is visible, exportable to PDF, and — where possible — reversible. This is the same ledger the scenario writes to live.
Facet 06
After the exercise, the workbench compares expected versus observed effects, intelligence accuracy, civilian-harm indicators, model error, and process gaps — then feeds lessons back into staff training and model governance, never autonomy.
Why this reaches the principal's desk
Framed for the Secretary of War, Deputy Secretary, and Chairman of the Joint Chiefs: the case for adopting responsible AI in targeting without ceding the human decision.
Machine-speed staff work compresses the path to a defensible brief from hours to minutes, letting commanders decide inside the adversary's timeline — without lowering the bar on rigor.
Humans set objectives, hold risk acceptance, and make the call. WARRANT makes that authority auditable — command responsibility becomes a record, not an assumption.
Every advancement is logged, reversible, and tied to law-of-war and ROE gates — defensible to oversight, allies, and the public, and aligned to the DoD AI principles.
Doctrine, policy & governance basis
The prototype labels the mission owner as Department of War per build request; source references retain their published DoD / Joint Staff titles.