Trains from visual input, C.A.S.E. learns user movements and automatically turns them into 3d-world actions, generating the code for things like grabbing objects. This makes prototyping feel natural and instant, cutting down on manual scripting so developers can focus on perfecting the overall experience.

C.A.S.E. learns from user movement data, providing developers with seamless pathfinding and obstacle avoidance, reducing the need for manually coded navigation systems. This helps developers create smarter, more realistic navigation with far less effort.

C.A.S.E. has been tailored to a variety of different genres, providing assistance but not limited to: horror, FPS and racing games (more models to come)

C.A.S.E. learns how people naturally move through and use spaces. Instead of manually programming every interactive element, designers can train the system on real movement patterns to automatically generate responsive environments—like doors that anticipate approach or lighting that adapts to occupancy. This creates smarter, more intuitive spaces while saving countless hours of manual scripting and adjustment.