Deep Inspection Collatio

An AI image comparison inspection system optimized for high-mix low-volume manufacturing.Deep Inspection Collatio

An AI image comparison inspection system that utilizes the huge amount of non-defective and defective product data required to run multi-product development with minimal work.
When performing inspections on various types of small lots, such as printed materials and semiconductor substrates, comparison inspections can be performed with significantly reduced false positives and negatives.
This system can be incorporated into existing production lines, and it will learn from every error to increase its decision-making accuracy.

Deep Inspection Collatio Features

Optimized for high-mix low-volume manufacturing

Collatio doesn’t require much good / defective product data to be put into use, so it can be introduced to sites where the number of production lots is low and the specifications change a little every time.

After installation, a variety of products can be developed smoothly with minimal labor.

One piece of good product data can be used by applying learning from other products. If there is an error, the AI will learn each time, constantly improving operational accuracy.

Can be installed into existing lines

Our product is not a package, it is a system that makes use of the customer’s current production line. With the capacity to design for a variety of different work sites, we offer products with long-term operation and upgrades in mind.

Three Steps of Comparative Inspection

  • STEP.1 Creating pair images

    Creating pair images of good quality and bad quality versions of the same parts in the same area.

  • STEP.2 Show defective areas

    Using Rist’s original comparative neural network, the AI learns the characteristics of good and bad areas.

  • STEP.3 From verification to installation

    Performing verifications and introducing it to the production line while actually running the systems. If provided with images, the AI can still detect OK and not OK examples of products it hasn’t previously learned.

    * Images are for illustration purposes.

case.01Abnormality detection in printed materials using comparative inspection


The AI can learn to recognize subtle color and shade differences due to printers and scanners, and printing abnormalities such as blurring, dirt, and scratches, identifying only abnormalities that need to be detected.

Installation Process

  1. 01Examination and Analysis

    The installation method is planned according to the end goal, whether it is new construction, or implementation into the customer’s products or existing production line.
    Feasibility will be examined based on a rough consultation that could occur via email, videoconference, or face to face. Feel free to get in touch with us and start the process.

  2. 02System Design

    After collecting data specific to the customer’s worksite, we devise an optimal learning algorithm, and then go through prototype development before entering main development and delivering the product.When necessary, we collaborate with companies in various fields to design and develop hardware than can handle special inspections.

  3. 03Result Measurement and Verification

    With the constructed line in action, we measure and verify result data, fine-tuning the AI program to optimize its performance.

  4. 04Beginning System Operation

    After installation, we continue to support customers through maintenance inspections and additional AI learning.
    We also offer consultations for more advanced inspections.