Orama Technologies offers an AI‑driven mixed‑reality platform that simulates close‑quarters combat using full‑body motion capture, 1:1 weapon replicas, and a 360° virtual environment with realistic ballistics. The system generates adaptive AI adversaries and provides instant after‑action review reports, all in a portable package that can be deployed anywhere for military and law‑enforcement training.
Funding
Funding not disclosed
Founders
Product
Problem
Live-fire close-quarters combat training requires real ammunition, hazardous environments, and extensive logistical support, limiting the frequency and realism of exercises for military, law‑enforcement, and allied forces. Traditional simulators often lack adaptive adversary behavior and detailed after‑action feedback, reducing their effectiveness for skill development.
Solution
Orama Technologies provides an AI‑driven mixed‑reality training platform that recreates live‑fire CQB scenarios without any physical risk. The system combines full‑body motion capture, 1:1 weapon replicas, and a 360° virtual environment to deliver realistic ballistics and physics. Integrated AI engines generate near‑peer adversaries that learn from each session, offering opponents that adapt tactics in real time. All actions are recorded and processed to produce immediate after‑action reviews, enabling operators to analyze decisions, movements, and shot placement instantly. The entire solution is field‑deployable in a single Pelican case, allowing training in any location from forward operating bases to police precincts.
Target Audience
Primary customers are military units, law‑enforcement agencies, and allied security forces that require realistic, low‑risk CQB training and rapid performance feedback.
Features
- Full‑body motion capture synchronized with 1:1 weapon replicas for authentic live‑fire fidelity
- Real‑time physics engine delivering accurate ballistics, recoil, and environmental interactions in a 360° mixed‑reality space
- Adaptive AI opponents powered by computer‑vision tracking and machine‑learning models that evolve tactics based on player behavior
- Automated capture of every round, movement, and decision, generating instant after‑action review (AAR) reports with performance metrics
- Portable, self‑contained system that fits in a Pelican case for rapid deployment in any training environment
- Compatibility with existing training facilities and command‑and‑control networks via standard data interfaces