A Multinational Manufacturer Fueled Asset Inspection Efficiency with C3 Generative AI
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Challenge
Historically, asset inspectors had to search across multiple systems for equipment inspection data, manually piecing together information from cloud storage and asset management platforms, as well as hundreds of scanned pages from legacy records. The process was lengthy and non-scalable, especially with records including handwritten notes and inconsistent document formats. Such constraints affected turnaround time, consistency, and accuracy, impacting timely equipment maintenance.
Solution
Over a few weeks, the C3 AI team collaborated with subject matter experts and asset inspectors to configure an AI-powered inspection data pipeline. This solution provided real-time, AI-generated summaries of equipment inspection data, along with historical document search, annotation, and retrieval capabilities. The platform integrated data from cloud storage and asset management systems, enabling inspectors to quickly locate relevant insights and access AI summaries with source links for deeper verification.
Project Highlights
- Unified data from 91 physical assets
- Integrated 70 years of non-digitized unstructured documents unified across seven structured data sources
- Reduced error risks during turnaround scoping from improved historical inspection data accessibility
About the Company
- $2.5+ billion annual revenue in 2023
- 700K+ barrels per day of refining
capacity - 28,000+ employees
Results
80%
Reduction in scoping turnaround times, allowing inspectors to complete tasks in hours instead of days.
70
years of non-digitized unstructured documents unified across seven structured data sources, allowing users to view consolidated asset history and identify risks and recommendations that were previously invisible to their data tools.
100%
of users reported that the solution significantly accelerates inspection scoping workflows and effectively surfaced critical technical data.
Solution Architecture
Proven results in weeks, not years
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