Speediance is expanding its connected fitness platform with a trio of proprietary AI models designed to understand movement, guide training decisions, and model how exercise and recovery choices could affect what comes next.
The company calls the models Votus, Oryn, and Somni. They work alongside AEVIS, an AI-powered experience layer intended to carry relevant information across workouts, recovery periods, sleep, nutrition, and daily schedules. Speediance says the broader goal is to build a fitness system that understands more than the workout currently on the screen.
Votus Analyzes How Users Move
Votus serves as Speediance’s movement-intelligence model. Using video from a single smartphone camera, it is designed to reconstruct human movement in 3D and analyze exercise technique as a movement takes place.
Speediance has demonstrated Votus for movement analysis and velocity-based training, pairing information such as repetition speed with more conventional workout data. The phone handles the visual input, leaving Votus to interpret what the athlete is doing.
For now, Speediance is demonstrating the technology inside its own fitness ecosystem rather than offering it as standalone software for conventional gyms.
Oryn Looks At Training, Recovery, Nutrition, And Sleep
Oryn focuses on exercise, nutrition, and sleep, using available context to help determine what type of training may make sense at a particular moment.
Rather than generating a workout from a prompt and calling it a day, Oryn is being developed to weigh a broader picture of the user. That could mean following the original training plan, reducing the workload, changing the session’s focus, or prioritizing recovery.
Somni takes a longer view. Speediance describes it as a human-state world-model research project that examines how different choices could influence future conditions such as fatigue, sleep, appetite, and trainable capacity. It is a technology preview, not a medical device.
AEVIS Gives The System A Memory




AEVIS is the connective layer tying these ideas together. It is designed to retain relevant context instead of treating each interaction like a fresh chatbot conversation.
That context can include training history, recovery signals, sleep, nutrition, and schedule changes. In one Speediance demonstration, AEVIS accounted for an upcoming six-hour round-trip drive by lowering the planned training load and placing greater focus on sleep and recovery. Afterward, workout information, movement video, and heart-rate data were used to reassess the user’s condition and shift the following plan toward mobility and active recovery.
The interesting part is less about one AI-generated recommendation and more about continuity. Fitness software has plenty of data already. Speediance wants that data to remember what happened yesterday before deciding what happens tomorrow.
New Hardware Fits Into The Bigger Fitness Platform

The AI work accompanies several newer Speediance products. Gym Monster 3 delivers up to 220 pounds of digital resistance across 19 cable positions, while Gym Monster Ultra raises that figure to 260 pounds and adds 33 cable positions.
Gym Nano puts up to 220 pounds of digital resistance into an 8.2-kilogram portable system, complete with velocity, power, and performance measurements. Speediance Strap adds a screen-free wearable to the mix, using greenteg Calera technology to track wrist-based core body temperature trends and provide added recovery context.
Speediance says deeper links between its AI systems and training hardware remain in development. AEVIS cannot currently control Gym Monster resistance autonomously, so the vision is still a roadmap rather than a fully automated coach living inside the machine.
The direction is clear: Speediance is moving beyond a single smart home gym toward a broader connected fitness platform spanning strength training, movement analysis, recovery sensing, and AI-guided decision-making.












