NAGARE verifies every kit before it reaches the line, right components, right sequence, right count. It checks what’s in the kit and what the operator did with it, so nothing incomplete or mis-packed moves downstream.
A missed or swapped part in manual kitting isn’t caught until assembly, or later. Without verification at the point of staging, that means rework, a line stoppage, or a kit that ships incomplete.
Our closed-loop system, NAGARE™, uses real-time video analytics to verify kitting processes, instantly track components and catch errors, and ensure every kit is right before it ships.
Kitting verification 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 kitting stations, confirm camera coverage, and scope the component list for kit-level verification.
The model trains on your actual parts and kit configurations, not a generic parts library. Training uses 120 minutes of footage.
Verification runs alongside your current process first, then is confirmed accurate before it goes live on your line. Deployment takes 4 weeks, with ROI payback in 6–12 months.
Bring your kits and your trickiest variants. We will scope a pilot on your line.
Comparison
When errors are caught
At assembly or at the customer
Post-pack, static camera gates
During packing, in real time
What it sees
Whatever the checker notices
Components, fixed positions only
Components and operator actions
New line or new kit setup
Retraining, weeks
Reprogramming, weeks
New kit variants configured in minutes
Hardware
Hand tools and checklists
Proprietary cameras and fixtures
Runs on your existing cameras
Traceability
Paper logs, if kept
Pass or fail report per unit
Video-backed report for every kit
First-Time-Right
Hope
Inspection after the fact
Right the first time, every shift
Discover how industry leaders achieve defect-free kits with Jidoka’s AI vision systems.
High-speed biscuit inspection with automated quality control:
Labelled bottle inspection with AI vision system and modular hardware:
Kitting inspection AI uses machine vision and deep learning to automatically verify that all components in a kit are present, correctly placed, and properly packaged before reaching the assembly line.
Yes, with video analytics, the system monitors both components and operator actions. It tracks the kit completeness, detects whether any part is missing or not, and validates the correct quantities during packaging. With AI‑enhanced package quality control, the post-packing quality checks can be eliminated completely.
The machine vision AI for packaging can train new operators as it displays step-by-step digital instructions, which helps the new operators to complete the packaging in the absence of a mentor. The AI can track sequence completion automatically and configure multiple variants easily. Integrating AI can improve efficiency by 30%.
Using machine vision for package completeness can reduce errors, minimize rework, prevent defective kits from reaching assembly, and speed up operator training. With these benefits, companies can lower production costs, higher throughput, and better product quality.
Yes. Once trained, the AI can inspect multiple kit types, adapt to new configurations, and scale across production lines or plants with minimal reconfiguration; all thanks to deep learning algorithms supporting kitting inspection.
As the AI inspection system is integrated in packaging lines, errors are flagged instantly as the kit moves through inspection, allowing operators to fix mistakes immediately and avoid downstream issues.
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