OpsCom · Adversary preparation
Train Against a Thinking Enemy.
AI-driven adversary preparation for tactical teams — measured.
Your training enemy is predictable.
Doctrine says the opposing force should be “difficult to template.”[1]
By the third iteration, your operators have templated it.
Predictable
your OPFOR, by iteration three
Opinion
the AAR standard today
Zero
objective performance data
Units don't lack reps. They lack a thinking enemy — and proof of readiness.
The evidence
Adversary quality decides outcomes.
TOPGUN, 1969
After the Ault Report, the Navy rebuilt training around dedicated dissimilar adversaries — the kill ratio over North Vietnam went from 2.42-to-1 to 12.5-to-1. The same report demanded an instrumented range for accurate debriefs.[2]
Deliberate practice
Expert performance is built by varied, progressively harder challenges with immediate feedback — not repetition of the familiar.[3]
Debriefs, done right
Across 46 studies, properly conducted debriefs improve performance by roughly 20–25%. Structure and evidence are what make them work.[4]
Red teams get captured
Predictable red teams stop challenging the organizations they serve.[5]
The science is settled. Team-level tooling is not.
The interactive demo
Generate a problem set. Vary it. Measure the result.
Everything below runs in your browser — synthetic content, drawn from a scenario-designer pool. It shows the loop, not the range.
Illustrative training demo — synthetic data
Scenario
Generate
Generate, plan, fight — then measure.
Generate
AI builds enemy COAs from threat doctrine and your venue — new every iteration.
Plan
Your team plans against each problem. Operators approve everything.
Fight
Professional OPFOR executes the problems live — differently, every run.
Measure
Instrumented performance and a source-traceable record.
Each rep harder than the last — because the enemy learns, on purpose.
Units already buy OPFOR.
Nobody varies it. Nobody measures it.
We do both.
Performance, not opinion.
- Decision latency under pressure
- Plan adherence — and adaptation
- Training frequency, before vs. after
- Debrief vs. ground truth, auto-flagged
- Automation bias (the humans-plus-AI system)
Cycle scorecard — illustrative
Team readiness score
0/ 100
Every claim traces to captured evidence. Trend it across the cycle.
Honest AARs. Defensible records.
Bodycam audio, radio logs and records-system data are the ground truth of every iteration — the system flags where the debrief diverges from what was captured, before a reviewer does.
For law enforcement
Source-traceable, audit-ready records your counsel can stand behind.
Human-approved
Explainable
Audited
Decision support, never decision replacement.
No autonomous action · no weapons integration · aligned with DoD Responsible AI principles
Proven in live operations
70%+
planning-time reduction, measured in deployment
2–4×
training frequency, measured in deployment
60+
operatives, three high-risk countries
United Nations close-protection deployment — commercial technology, not a concept.
Built for training budgets.
Tier
Pilot
one team, one cycle
$25k–$50k
Recommended
Pre-deployment program
recurring iterations
from $150k / yr
Tier
Enterprise
multiple teams
$500k+
Sold per team · one training cycle to start · expansion inside existing contracts.
Let's put it on the range.
One team · one pre-deployment cycle · a measured answer.
DY Kim, CEO · dy@opscom.io · opscom.io
Demo data is synthetic and illustrative. OpsCom, Corp. Metrics cited from prior deployment; methodology available on request.
Sources
- [1] TC 7-100.2, Opposing Force Tactics. Headquarters, Department of the Army (2011).
- [2] U.S. Naval Institute Proceedings (1986), “Topgun: Getting It Right”; F. Ault, Report of the Air-to-Air Missile System Capability Review (1968).
- [3] Ericsson, Krampe & Tesch-Römer (1993). “The Role of Deliberate Practice in the Acquisition of Expert Performance.” Psychological Review, 100(3).
- [4] Tannenbaum & Cerasoli (2013). “Do Team and Individual Debriefs Enhance Performance? A Meta-Analysis.” Human Factors, 55(1).
- [5] Zenko, M. (2015). Red Team: How to Succeed by Thinking Like the Enemy. Basic Books.