Modern battle management isn’t short on data; it’s short on time.
In high-tempo operations, battle managers must synthesize fragmented inputs from across domains (air, space, cyber, electromagnetic spectrum), align decisions to commander intent, confirm compliance with constraints like ROE, and execute within shrinking time windows. The difference between success and failure is often measured in minutes or seconds.
That’s why the U.S. Air Force’s Advanced Battle Management System (ABMS) program continues to invest in Decision Advantage Sprint for Human-Machine Teaming (DASH): rapid, operator-centered experiments designed to prove how humans and machines can collaborate to generate better decisions faster.
At DASH, Rackner competed in the Air Force’s code challenge in Las Vegas, building next-generation command and control (C2) software to help deliver warfighters a real decision advantage.
Legacy C2 systems were built for a different era. They often assume stable communications, predictable timelines, and human-driven planning cycles, leaving operators to manually piece together the picture from ISR tracks, chat logs, voice comms, and mission artifacts.
Rackner is addressing that gap by developing REAPER, a modular suite of battle management microservices purpose-built to enable AI-augmented, explainable decision logic aligned to the Transformational Model for Battle Management.
REAPER is designed to integrate into operational pipelines as composable decision functions, each microservice responsible for a specific part of the decision chain, and able to connect to others through shared schemas and event-driven interfaces.
The goal of DASH isn’t to replace battle managers; it’s to give them better options, faster.
REAPER follows a human-on-the-loop approach: operators stay in command while the system reduces cognitive load, ranks viable options, and surfaces clear justification to support rapid validation and action.
That trust layer matters. REAPER’s interface design was shaped by direct operator feedback from prior DASH events and emphasizes clarity, speed, and low-friction workflows, including the ability to review and send operational actions through chat with minimal overhead.
At DASH, Rackner’s work centered on the Battle Management need to generate Battle Courses of Action (COAs), not as a single “best answer,” but as a structured set of executable options that remain viable as the fight changes.
REAPER’s Generate Battle COAs (GBC) decision function takes upstream recommendations and transforms them into coordinated, time-sensitive plans.
In practice, that means:
consuming BattleEffects and Matched Effectors from earlier decision functions,
incorporating operational constraints like timing, task conflicts, and ROE,
and outputting a ranked set of COAs with confidence scoring and tradeoff rationale.
Rather than producing a static plan, GBC models COAs using a hypergraph-based approach that captures dependencies and alternate paths, enabling continuous updates as the tactical picture shifts.
ABMS demands modularity, resilience, and integration.
GBC is designed as a containerized microservice and exposes both REST and event-driven interfaces (including real-time streaming patterns) so it can integrate into diverse battle management pipelines without custom adapters.
Equally important: REAPER is engineered to be vendor-agnostic. While it can consume matched effector streams from Rackner’s MEF module, it is designed to ingest compliant inputs from any upstream decision function, supporting interoperability across organizations and coalitions.
What does “decision advantage” look like in real terms?
It looks like:
options generated inside the decision window,
clear explanations for why choices are ranked the way they are,
operator control and validation baked into the workflow,
and the ability to adapt when the battlespace changes unexpectedly.
As our team shared internally after the event, DASH was the most complex DASH iteration yet, and Rackner delivered a tool that helped operators generate battle COAs significantly faster, while still enabling human oversight.
DASH continues to prove that human-machine teaming is most effective when it’s built around:
real operator workflows,
explainability and trust,
low-latency performance,
and open integration patterns.
Rackner is proud to contribute to the ABMS mission and to keep building battle management software that moves at the speed modern operations demand, without compromising human control.
If you’re interested in future DASH events or the REAPER battle management microservice roadmap, reach out to our team.