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Look
A worker looks at a bin, valve, defect, panel, landing zone, or machine. Attention becomes the first signal, without reaching for a scanner, tablet, or joystick.
A hands-free intent layer for industrial work.
Workers look at bins, panels, valves, defects, drones, and machines all day. Eta Visor turns those moments of attention into structured commands, logs, and robot-ready signals without scanners, tablets, joysticks, GPS, or scene cameras.
Field teams still stop to scan, tap, radio, annotate, confirm, and re-enter context into separate systems. Robots and drones may be autonomous, but they still need humans to tell them what matters. Eta Visor makes attention itself the input.
People naturally look at the thing they are about to pick, inspect, repair, confirm, or command. Eta Visor treats that attention as a signal, turning gaze, motion, and context into a reliable interface for physical operations.
No scanner, tablet, joystick, or teach pendant required for target selection.
Structured events for robot tasks, drone targets, inspection logs, and safety dashboards.
Built for indoor, occluded, dusty, dark, and GPS-denied workflows where conventional tracking struggles.
Eta Visor uses eye tracking, motion sensing, and on-board intelligence to understand what the worker is focused on and convert it into useful output: a target, a log entry, a robot command, or a safety signal.
A worker looks at a bin, valve, defect, panel, landing zone, or machine. Attention becomes the first signal, without reaching for a scanner, tablet, or joystick.
A short dwell, gesture, button, or policy rule separates deliberate intent from casual glances. The system only acts when confidence is high enough.
Eta combines gaze, motion, and context to identify the target and estimate confidence. The output is not raw eye data, it is a usable intent event.
The event is sent to the right endpoint: a robot task, drone target, inspection record, safety dashboard, warehouse system, or research pipeline.
A robot dispatches, a drone captures, a work order opens, a pick is confirmed, or a supervisor is alerted. The worker stays focused on the physical task.
Every action carries target, time, confidence, operator context, and optional safety state. Operations teams get an audit trail without extra manual logging.
Command history and confidence data reveal workflow bottlenecks, missed assets, fatigue patterns, and opportunities to automate the next step.
Eta outputs the signals operations teams actually need: what the worker selected, how confident the system was, where it happened, and what downstream action was triggered.
Each workflow starts the same way: a worker looks at what matters. Eta Visor turns that moment of attention into location, logging, or command without adding another handheld device to the job.
An inspector looks at a flange, gauge, leak, or defect. Eta creates a time-stamped inspection event with target, location, confidence, and follow-up status without stopping to write notes or tap through a tablet.
A picker looks at the next bin and confirms by dwell. The system sends a target event to the WMS or robot fleet so picks, AGV dispatch, and audit logs stay synchronized while both hands stay on the job.
An operator looks at a valve, roof edge, panel, or confined-space inspection point. Eta sends a target request to the drone autonomy stack, which handles safe approach, capture, and return.
Eta Visor turns attention into structured events that can be routed to drones, robots, dashboards, warehouse systems, maintenance systems, or research pipelines. The same wearable interface can support inspection, picking, robot dispatch, drone tasking, and operator-state monitoring.
An operator looks at an inspection point and Eta sends a structured target request to the drone autonomy stack. MAVLink support lets the flight system receive the event in a format it already understands.
A picker, technician, or supervisor looks at the next useful target. Eta publishes intent, pose, and confidence into ROS2-ready streams for robots, AGVs, and automation systems.
The same attention stream can produce time-locked intent, fixation, and operator-state events for safety monitoring, research workflows, and neuroadaptive systems.
Scanners, tablets, controllers, AR headsets, and eye trackers each solve one piece of the workflow. Eta connects the full loop: what the worker is focused on, what action they intend, and which machine or system should receive it.
The practical layer is simple: attention and motion go in, structured events come out. Eta is designed to connect with the systems teams already use, not force another screen into the workflow.
We are opening pilot conversations with teams that want to remove scanners, tablets, joysticks, and manual logging from physical workflows, starting with warehouse robotics, industrial inspection, and GPS-denied drone operations.