• The Kiara Web Inspection Systems

    Total Control on Quality for You and Your Customers. Defect Identification, Categorisation and Digitisation for Quality and Analytics
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Accurate and Efficient Web Inspection Systems with AI Technology

Kiara High-performance web inspection system can detect a wide range of defects at high speed in real time. It generates a comprehensive defect map that helps system operators optimize the production process, and ensures uncompromising quality control.

Our system is designed for seamless integration into any production line. Used by many major corporations and production plants across India for inspecting Textiles, Labels, Sheets, and more; our system has proven to reduce waste by 70% and ensure 100% quality control.

Introducing the Kiara Web Inspection System

Defected products can damage your brand reputation and business. Companies rely on rigorous quality checks, but manual inspections are time-consuming and prone to errors.
  • The Kiara Web Inspection system ensures that your fabric quality is always perfect. This AI-based vision system can detect even the most minute defects and send alerts in real-time.
  • The system integrates as a part of your production line. As such, it helps automate the production process by optimally removing defective parts using AI assistance.
  • Kiara web inspection system is very easy to operate and requires minimal training. 
  • The Kiara system can become one of your trusted employee and save millions in waste material, costly recalls, and hours of manual inspection. 

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How does Kiara Web Inspection System Works?

Kiara Web Inspection system simplifies the complex process of defect detection and minimizing wastage of material.

How does Kiara Web Inspection System Works?

Defect Detection

The Kiara Web Inspection system constantly monitors the source object like textile, sheet, label, etc. It looks for major and minor defects with 100% accuracy.

Self Learning

The Web Inspection System (KWIS) constantly learns and improves itself based on the defect types and detections. Thanks to self learning, the system does not need intervention and calibration as it adapts to the defect type and detection. 

Reporting and Action

Upon defect detection, Kiara autonomously triggers alerts, halts operations if necessary, or executes pre-programmed actions Further more, it provides a detailed report of the defect in form of defect map and markings.


The Kiara Web Inspection System provides a detailed analytics about the inspection process. It helps business owners analyze the efficiency of production process, machine, and system operator. 

KWIS - Product Suite 

KWIS - Technical Textile
KWIS - Roll Master Review
Flexible Intermediate Bulk Container Inspection

Flexible Intermediate Bulk Container Inspection

Retrofits on existing cutting machines, that’ll capture all the defects and provide optimum cut point. Consists of pre trained AI model that helps to categorize defects which is useful in creating custom recipes as per customer specification. KWIS conducts high-speed inspections, scanning at the rate of 120 meters per minute

KWIS - Technical Textile
KWIS - Roll Inspection System

KWIS - Roll Inspection System

KWIS - Roll to Roll uses a hybrid approach of traditional and AI technologies to perform high-speed inspection on roll winding and rewinding machines, with all data captured digitally. For each variant, a master pattern is created and used by intelligent pattern matching to identify deviations. AI then classifies defect categories, becoming smarter as more data is fed

KWIS - Roll Master Review
KWIS - Roll Master Review Software

KWIS - Roll Master Review Software 

KWIS - Roll Master software provides digital access to all data captured from KWIS , including defect images and locations. This enables roll grading and evaluation, with features such as a digital defect map, filters to select defect types, roll-wise defect categorization, and data preparation to stop at specified defect locations.

Kiara Web Inspection System Features

Accurate Defect Detection

High detection for even the smallest defects

Improved accuracy over time through machine learning algorithms

Inspect Up to 150 Meters/Minute

Fast detection, Increased productivity

Minimized production downtime and delays

Deep Learning Based Model

Efficient processing 

Recognize and classify a wide range of defects

Precise AI Vision System

Precise defect identification

Adapts to changing production needs and requirements

Self-Learning  Software

Continuous improvement, adaptive defect detection

Reduces the need for manual intervention and calibration


Space saving, easy integration into existing production lines

Reduces installation and maintenance costs


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Our Clients

Impact of Our Relentless Pursuit of Progress

deployed across 18+ states


18+ States

until now

over 1000 types of defects detected



kinds of defects detected

89000+ meters of fabric detected



meters of fabric

1,00,00,000+ rupees saved



in wastage

Frequently Asked Questions

What are some of the benefits of using an AI vision system for web inspection?

AI vision systems learn continuously and adapt to your changing requirements of inspection. These automated inspection systems help to improve the accuracy and speed of web inspection, reduce labor costs, and improve product quality.

What is the difference between AI vision and traditional vision for web inspection?

AI vision is machine learning-based, meaning that it learns by examples and we provide it with a large dataset of defect-marked images. Traditional vision, on the other hand, is rule-based, meaning that it uses a set of pre-defined rules to identify defects in images.

What are the advantages of AI vision over traditional vision for web inspection?

AI vision is more accurate, flexible, and provides defect categorization. It is also more robust to changes in lighting, noise, and other environmental factors. Additionally, AI vision can be easily adapted to identify new types of defects, while traditional vision is more difficult to adapt.

What are the most common types of defects in web inspection?

The most common types of defects in web inspection include structural defects, like holes, warp damage, weft damage, wrinkles, surface defects like contamination, foreign particles, etc. In some cases, edge damage, tears, cuts, and lamination faults are also present.

What is the difference between master comparison and defect teaching?

Master comparison is a traditional defect identification method which works by comparing an image of the product to a master image of a perfect product. Defect teaching is a method of training an AI vision system to identify defects by manually labeling defects in a set of images.

Which methods are used in AI vision system for web inspection?

Object detection, image segmentation, and image classification are some techniques that are used in AI Vision Systems for web inspection. Object detections locate the position in an image, image segmentation finds the boundaries of the defects, and image classification provides the categorization.

Can I use a hybrid approach that combines master comparison and defect teaching to train my AI vision system for web inspection?

Yes, you can use a hybrid approach that combines master comparison and defect teaching to train your AI vision system for web inspection. This presents the best of both worlds when it comes to mixing AI based approaches with traditional methods.