Revolutionizing a 1000 year old process of inspecting rope for damage through applied deep learning.

Meet Scope

The Problem

Worldwide, the standard best practice to determine if a rope is safe for use is manual visual inspection. People look at a rope and decide if it is safe to use. This is an incalculable risk. Further, because manual visual inspection is subjective and qualitative, a safe level of compliance cannot be realized or maintained.

The Solution

Scope builds automated inspection systems for critical rope applications, utilizing deep learning technology to identify and assess line damage. Our systems enable operators to take data-driven actions to repair or replace failing lines before catastrophic incidents occur. This is accomplished in real-time, with a level of accuracy exceeding that of visual inspection, with software that is continuously learning.

Increase Safety with Enhanced Line Health Inspections

With the ability to predict within 5% of actual Residual Break Strength (RBS), Scope systems consistently outperform manual inspection when predicting RBS and identifying anomalies. Early detection of wear and tear, damage or defects reduces the likelihood of accidents and equipment failures due to rope deterioration.

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Increase Inspection Efficiency Across your Fleet

The ability to accurately inspect a line does not have to be siloed to specific individuals or locations. With Scope, operators have the ability to inspect, assess and manage their fleet across multiple locations simultaneously, saving time and labor costs compared to manual processes.

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Confidently Comply with Industry Standards and Regulations

Comply with industry standards and regulations by demonstrating that all synthetic ropes are consistently maintained to a safety factor and in good working condition, reducing the risk of accidents and ensuring a safer working environment.

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