One camera. Every action. Every deviation.

You don't find out something was skipped until the end. By then it's a rework loop, a batch to sort, or a call from a customer who found it first.

Most of it starts with a hand. The American Society for Quality puts the cost of quality failures at around fifteen percent of revenue, and on manual lines the largest share of that traces back to execution rather than to suppliers or design.

Operator Vision checks sequence and execution on every cycle. Missing components, steps run out of order, wrong part, wrong tool, wrong label on the carton, a left-hand part going into a right-hand box. Operator Vision also enforces the checks that get short-changed when parts stack up: minimum inspection dwell time, no skipped gauge check.

When something fires, the alert reaches the bench first, so the operator gets the chance to fix it while the piece is still at the station. You get the video attached. Root cause analysis that used to hold a room until eight at night resolves in minutes.

Dozens of stations, multiple shifts, and one of you. You already know which station is the bottleneck. What you don't have is the coverage to prove it, or the weeks it takes to study it properly with two people, one working and one watching.

And the study lies anyway. The moment an operator knows they're on the clock, the work changes: pace, sequence, sometimes even the PPE. It takes about a week of the camera just sitting there before the data starts describing the job rather than the audit.

Operator Vision runs a continuous time study on every station it watches. Average, minimum, and maximum time per step, sliced by step, shift, and station, with video attached to every outlier. That thirty-minute cycle stops being an investigation and becomes a click.

Assembler AI builds to a simple target: give a continuous improvement engineer back half the time they currently spend on manual studies.

Your reporting refreshes overnight and tells you what already happened. Nothing tells you where the work is sitting right now.

Most plants know their build time and their flow time, and know the gap between them is mostly waiting. What almost nobody has is the step-level detail underneath: which station the queue forms at, which step drifts, and on which shift.

Operator Vision gives you flow and execution data across every station it watches, live, with the ability to compare shifts, cells, and stations against each other. You find out which line is genuinely fastest, and why, with evidence rather than anecdote.

Operator Vision also flags the moment someone does what the procedure says not to. A part picked up off the floor in a clean room, a step into a zone that should stay clear, a piece set down where it doesn't belong. The alert reaches your supervisors with the video attached, so catching it stops depending on who happened to be walking past.

The same data answers the question finance asks. Scrap and rework carry a shop rate, and every one of them ties back to the specific step that produced it.

A new hire takes months to build at the rate of your most experienced operator, and most of that time is spent learning by correction after the fact. Operator Vision puts the guidance at the bench instead, so the feedback arrives during the build rather than at a review weeks later.

It works the same way for the method itself. When one operator consistently runs a step faster and cleaner than everyone else, you can see exactly how, and that becomes the standard everyone learns.

Operator Vision puts guidance on a screen at the station: live step guidance, and a way to flag a missing part or a bad tool straight to engineering. If your floor has opinions about what belongs on that screen, that is exactly the conversation we want.

The camera reads the work, not the worker. Faces are blurred by default. We don't collect operator names or IDs by default, and we don't sell an employee monitoring tool. The analysis runs on the process, and the data comes back tied to a station and a shift, not to a person.

The footage protects your operators too. When a defect surfaces three stations down, the operator who did the job right has the record. When the work instructions are wrong and the operator found the better way, the video is the argument.