Caterpillar

Solution

Caterpillar describes an in-house AI implementation spanning machine-learning-based condition monitoring and generative AI assistance for service workflows. In the field, machine data from Cat-connected assets feeds Caterpillar's Condition Monitoring suite, which Cat dealers use to detect issues and recommend service or maintenance based on data from the machine itself. For the advisor workflow, incoming asset data and information pulled from multiple systems are analyzed and automatically prepared into a concise report. Caterpillar then applies GenAI to summarize the prepared data and create a draft recommendation before a human reviewer acts on it. Condition Monitoring Advisors review, approve, or edit the recommendation, keeping a human in the loop while reducing manual preparation time. Separately, Caterpillar developers use GenAI to query large proprietary information collections and retrieve practical answers faster than manual document review.

Data flow

Data from Cat-connected assets and other internal systems enters Caterpillar's Condition Monitoring workflow, where machine-learning-based analysis identifies issues and assembles the relevant context. GenAI then summarizes the prepared inputs into a concise report and drafts a recommendation, which a Condition Monitoring Advisor reviews, edits if needed, and uses to support customer service guidance.