A global chemicals and materials company struggled with complex, fragmented data across characterization and test rig systems, leading to inconsistent macros, difficult script updates, and delays of days between testing and analysis. To address this, the team ran a three-month Luma proof of concept that automated data ingestion, standardized outputs, and enabled low-code visual analytics workflows across both typical data such as NMR and atypical test rig data. The evaluation finished ahead of schedule and delivered measurable impact, enabling test teams to make decisions about 10 percent faster and application teams up to 80 percent faster. Standardized workflows also improved data visibility, reuse, and scalability.

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