Jidoka’s NAGARE AI trains operators at the station and scores skill from the work itself, on the cameras you already have. No classroom-to-floor gap, no mentor bottlenecks, no subjective sign-offs, just operators who reach standard faster, with proof.
Every open headcount and every green operator costs output until competency arrives. Training that depends on who is free to mentor, and sign-offs that depend on opinion, make that wait longer than it needs to be.
Our closed-loop system, NAGARE™, uses real-time video analytics to guide operators as they learn, score skill from actual work, and keep the whole workforce’s competency current.
See it running on your line
Tell our engineers which skills you assess today and they will walk you through implementation, timelines and cost for your line.
Learn More - Talk to our expertSee it running on your line
Tell our engineers how onboarding runs today and they will walk you through implementation, timelines and cost for your line.
Learn More - Talk to our expertSee it running on your line
Tell our engineers which motions matter most and they will walk you through implementation, timelines and cost for your line.
Learn More - Talk to our expertSee it running on your line
Tell our engineers how feedback reaches operators today and they will walk you through implementation, timelines and cost for your line.
Learn More - Talk to our expertSee it running on your line
Tell our engineers where errors repeat today and they will walk you through implementation, timelines and cost for your line.
Learn More - Talk to our expertOperator training runs on the cameras you already have at your stations. No pilot line, no new hardware to install. We have mapped this deployment before, which is what makes it fast now.
We walk your stations, confirm camera coverage, and scope the skills and steps to assess.
The model trains on your actual steps, stations, and best-practice cycles, not a generic action library. Training uses 120 minutes of footage.
Assessment runs alongside your current sign-offs first, then is confirmed accurate before your matrix depends on it. Deployment takes 4 weeks, with ROI payback in 6–12 months.
Bring your longest onboarding and your scarcest skill. We will scope a pilot on your line.
Comparison
When skill gaps are caught
At the annual review, or in the scrap bin
At test stations, off the line
On the line, every cycle
What it sees
Whatever the assessor remembers
Test results, not real work
Real work and operator actions
New skill or station setup
Shadowing, weeks
New test rigs, weeks
New skills configured in minutes
Hardware
Clipboards and sign-off sheets
Test rigs and simulators
Runs on your existing cameras
Traceability
Paper matrices, updated yearly
Test scores, point in time
Video-backed record per operator
Competency confidence
Hope
As of the last test
Continuous, every cycle, every shift
Discover how industry leaders build production-ready teams with Jidoka’s AI vision systems.
High-speed biscuit inspection with automated quality control:
Labelled bottle inspection with AI vision system and modular hardware:
It scores operator skill from the work itself. Camera-based AI watches real cycles on the line and measures accuracy, speed, and sequence against the standard, so competency is proven by observed performance rather than a written test or an assessor’s opinion.
A skills matrix records what someone decided about an operator, and an LMS records which courses they completed. Neither verifies what happens on the line. NAGARE feeds the matrix from observed work, so skill levels reflect current, real performance instead of last year’s sign-off.
New operators learn on the line with step-by-step guidance and instant correction, without waiting for a mentor to be free. Errors are fixed the moment they happen, coaching targets each operator’s actual skill gaps, and Jidoka deployments have measured an 80% improvement in training effectiveness.
Yes. The system assesses the process, not the person: the same objective criteria apply to everyone, scoring is standardized rather than opinion-based, and worker privacy is protected throughout. Operators get fair, data-backed development instead of one supervisor’s impression.
NAGARE analyses every cycle an operator runs and identifies the steps where their errors repeat. Supervisors see a per-operator picture of recurring mistakes, so coaching targets the exact step or motion that needs correcting instead of repeating generic refresher sessions for everyone.
No. It removes the repetitive load from trainers, the shadowing, the checking, the paperwork, so they spend their time on high-value coaching. The system handles monitoring, error detection, and feedback around the clock.
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