From Doctrine to Decision. For years, operational planning and emergency response systems have relied on static rules, hardcoded protocols, and human judgment—often under pressure and with limited information.
We’re exploring a different path: training AI to reason like a real tactical team.
Instead of using massive volumes of generic data, we are working with domain-specific doctrine—from regional emergency protocols to military planning manuals—to build decision-support agents capable of:
– Interpreting operational courses of action
– Evaluating dependencies between tasks and resources
– Recommending alternatives aligned with command intent
– Explaining the rationale behind each recommendation
This requires a rarely combined set of capabilities:
– Language models that understand tactical jargon and operational logic
– Structured representations of plans, missions, and scenarios
– Integration with maps, sensors, and real-time communication systems
Rather than “automating decisions,” our goal is to build a co-pilot that understands how decisions are made in practice.
At XRF, we treat tactical AI not just as a technical challenge, but as an operational, ethical, and strategic responsibility. That’s why we are combining doctrinal training, immersive simulation, and field-based validation before any real-world deployment.
If you’re interested in how we’re building AI that can understand real-world mission logic, we’d be happy to show you.
