AI Vision for Time-in-Motion

Traversal's Vision AI Platform / Time and Motion

Vision AI for High-Touch Workflow Improvement.

AI Vision for Production Flow

Subtask management can enable high-touch ergonomic workflows to be optimised.

Time-in-motion studies are a longstanding tool for designing manufacturing processes. However, the traditional approach for time-in-motion studies is tedious and manual.

Traversal's Vision AI Platform automates this process, for optimisation of high-touch industrial workflows.

We transform video into structured datasets through Scene Understanding. Our Event Builder interface enables customisable events to be added.

Transforming Video into Comprehensible Reports

Our Scene Understanding technology transforms video into structured datasets. We present these as comprehensible reports, which can be used to inform Lean initiatives.

Hypothetical Case Study


COGS (of an ergonomically-intensive workflow)


*Reduction In Waiting and Excess Motion



Margin Enhancement

*Hypothetical, this scenario is provided for illustrative purposes only, the accuracy and applicability of this scenario may be influenced by unique factors inherent to each user's environment and practices.

Inference Capability

Tool-On Time

Visual Inference of Tool-On Time (e.g. Welder Arc-On)

Repositoning Time

Visual Inference of Repositioning Time (e.g. Time spent climbing a ladder)

Reloading Time

Visual Inference of Reloading Time (e.g. Time spent to reload a tool)

Preparation Time

Visual Inference of Preparation Time (e.g. Time spent to prepare a tool)

Wait Time

Visual Inference of Wait Time (e.g. Time spent waiting for materials to arrive)

Spaghetti Analysis

Visual Inference of time spent moving between workstations

Pixel Privacy

Traversal has developed camera technology to preserve the privacy of individuals in visual scenes.
We pseudonymise our data, and remove individually identifying features, including blurring faces.