The Speediance Gym Monster platform is moving beyond digital resistance. At a launch event in Los Angeles, the company presented new equipment alongside AI tools designed to analyse movement, adjust training decisions and connect workout data with recovery information.
Speediance Gym Monster and Votus
Speediance demonstrated Votus using the camera on a standard smartphone. The system can reconstruct exercise movement in 3D, assess how repetitions are performed and add velocity data to the information already collected during a workout.
That could give home athletes feedback on technique without requiring body-mounted sensors. It may also help users identify when form deteriorates and better understand their limits during a session.
The company currently presents Votus as part of its own fitness ecosystem rather than standalone software for use in conventional gyms.
New Hardware, More Training Data
Gym Monster 3 delivers up to 220 pounds of digital resistance across 19 cable positions. Gym Monster Ultra raises that figure to 260 pounds and adds 33 cable positions, a vertical high lat pulldown, a multi-grip pull-up setup and an adjustable thigh restraint.
Both systems use digitally controlled resistance that can change throughout a movement and support training modes that are difficult to reproduce with traditional plates. During testing, the cable resistance was described as especially smooth, although stronger athletes may still exceed the Ultra’s current limit on some exercises.
Gym Nano offers a smaller alternative, weighing 8.2 kilograms while producing up to 220 pounds of digital resistance. It also records velocity and power, with assessments including peak force, rate of force development and left-to-right asymmetry.
From Workout Tracking to Adaptation
Speediance’s wider strategy includes Oryn, which focuses on decisions around exercise, nutrition and sleep, and AEVIS, which is intended to connect information across the system.
In one demonstration, a planned six-hour round trip led AEVIS to reduce training load and place greater emphasis on sleep and recovery. Later workout information, including movement footage and heart rate data, could then inform the next session.
Somni remains an earlier research project exploring how choices may affect fatigue, sleep, appetite and future training capacity. Speediance described the long-term ambition as a system that can sense, decide, act and learn, while acknowledging that the deeper connections between its software and hardware are still under development.