AI-Driven Defects Detection
with 95% Accuracy

Built on Gramex low-code platform that
is 30% faster to deploy

PepsiCo & BMW are leveraging defect detection with AI. Are you?

McKinsey predicts that, by 2025, Industry 4.0 applications & other defect detection solutions will deliver a potential value of USD 3.7 trillion to manufacturers. Do you have a winning defect detection strategy yet?

70% of businesses are experimenting with machine vision-driven defect detection systems. Is your defect detection delivering business success?

Only 30% of companies can reap the benefits of Industry 4.0 solutions at scale. Are you one of them?

Use-Cases of Defect Detection

Automatic inspections

Accelerate quality control & evaluation of
equipment such as piping, pressure vessels,
& storage tanks

Object recognition

Identifying objects inside images & videos
for analyses, counting, etc. Locate, label, &
classify items with great precision.

Supply chain & logistics

Help design workflows that address
supply chain challenges across
organizations of all sizes

Perishable goods grading

Classify perishable items according to size,
color, & freshness. Identify defects &
spoilage. Facilitate quality assurance.


Manufacturers benefit from
reduced labor and other
operational costs

Production volume
increase without
compromising quality

Preventing defective parts from
delaying assembly lines
through early error detection

Improved manufacturing
efficiency and reduced
turnaround times

Delivering better
accuracy rates than
the human eye

Identifying patterns in historical
data to predict & improve future
production processes

AI visual inspection works in 4 easy steps

We automate end-to-end process implementation for you, removing the intermediaries & ensuring that no manual
intervention is required. We offer a turnkey solution that easily integrates with your existing processes.

To collect the data, all you need is a camera, high-speed internet & storage space. Our data analytics model can be
trained to detect defects with a high degree of accuracy.

Step 1

Install cameras in the
production line

Identify right location to install the cameras and maintain proper distance & angle for a clean shot

Step 2

Capture & store
the images

Capture 200+ images for defect-free & defective products, and label the images.

Step 3

Train analytics

Feed the analytics engine with labeled images. Train the model to analyze the photos & detect flaws.

Step 4

Deploy the

Implement the solution in the production line and scale it as and when required