The published scientific literature is a rich, continuously growing record of measurements, correlations, and observations that modern AI tools can now make accessible in new ways. The Materials Explorer Pipeline digests collections of scientific papers into a structured, queryable database, producing sample records with full provenance and confidence, making them interactively explorable, and surfacing hypothesis candidates for scientist review. Each extracted record is a self-contained, portable unit of knowledge, carrying the measurements, research details, and source citations needed to use and cite the data appropriately. The Pipeline is demonstrated on recent superconducting qubit materials literature of the Co-design Center for Quantum Advantage, a DOE National Quantum Information Science Research Center, producing a corpus of 233 samples across 10 material classes. The Pipeline architecture is domain-agnostic and designed to be readily portable to other scientific domains.

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