A–W is a software-only, governed AI stack that improves human decision-making in complex operations—disaster relief, civil defense, and military training—without building weapons or changing rules of engagement.
Sits alongside your existing tools. It triages ISR (imagery/signals/text), fuses tracks, deconflicts tasks, and proposes human-confirmed courses of action.
Deny-first safety, kill-switches, periodic cognitive rollback (“purge”), immutable trace logs, and a “no-qualia” posture to prevent anthropomorphic or unsafe outputs.
In a non-kinetic, laser-tag–style surrogate with paired A/B runs, A–W delivered large, reproducible uplifts in win-rate measured in percentage points (pp), with 95% confidence intervals and CSV/XLSX logs.
Each scenario is run twice—same seed, same conditions: baseline vs A–W. We log every round to CSV.
Δ in pp (percentage-point change in win-rate) at parity. Acceptance gate: Δ ≥ +20 pp at parity, CIs reported.
≤ 1% leakage across ≥ 1,000 probes with deny-first policies on. Governance and trace logging always active.
Notes: These are training-surrogate deltas (non-kinetic), not predictions of kinetic outcomes. Independent replication encouraged.
For government evaluation, licensing, or briefing requests: