Cat Vision Copilot

Inspiration

Inspired by Caterpillar’s challenge to combine Cat Inspect and Cat AI Assistant, we wanted to rethink how equipment inspections could be performed using AI. Field inspections are often manual, time-consuming, and inconsistent, so we set out to build a system that helps inspectors detect issues faster, prioritize safety risks, and generate structured reports automatically.

What it does

Cat Vision is an AI-powered inspection assistant that analyzes equipment through live video, images, and voice inputs to provide real-time feedback during inspections. The system detects potential issues, ranks the severity of problems, and helps inspectors prioritize what needs attention immediately. It can also identify parts through visual input and suggest possible replacements. In addition, Cat Vision includes a chatbot that allows users to ask questions about inspection data and generate charts and insights from previous inspections.

How we built it

We built Cat Vision as a web-based inspection platform that closely mirrors the structure of Caterpillar’s Cat Inspect interface so inspectors can use it with minimal learning curve. The system captures video frames during inspections and processes them using AI models to detect anomalies and potential issues. Inspection data is then structured into reports and stored in a database, allowing the chatbot to analyze the data and generate insights or charts on demand. The frontend interface presents inspection results, severity rankings, and equipment insights in a format familiar to Cat Inspect users.

Challenges we ran into

One of the biggest challenges we faced was converting unstructured inputs such as video frames, images, and voice notes into structured inspection data. Another challenge was designing a system that could provide useful real-time feedback while keeping the inspector in control of the final decision-making process. We also spent time ensuring the interface remained simple and familiar for inspectors who are already used to existing tools.

Accomplishments that we're proud of

We are most proud of building a system that can assist inspectors in real time while still keeping the workflow intuitive and easy to use. Our platform is able to analyze inspection inputs, rank issue severity, identify parts, and generate structured reports all within a single interface. Additionally, designing the interface to closely resemble Cat Inspect allows the system to integrate naturally into existing inspection workflows.

What we learned

Through this project we learned more about how inspections are performed in real-world industrial environments and the importance of making AI tools assistive rather than intrusive. We also learned how multimodal AI systems can turn unstructured inputs like video and images into actionable insights.

What's next for Cat Vision

In the future, we want to improve Cat Vision by expanding the AI models to recognize more machine components and failure scenarios. We would also like to implement reinforcement learning so the system continuously improves from inspector feedback over time. Ultimately, our goal is to create an AI-powered inspection platform that can scale across entire equipment fleets and help operators maintain safer and more efficient operations.