A technical guide to the quality dimensions that determine whether an industrial dataset is useful for model training, including completeness, temporal resolution, and annotation accuracy.
Comparing the effectiveness of synthetically generated industrial data against authentic operational data for AI training, and what this means for data brokerage.
Exploring why labeling sensor readings, equipment logs, and process data requires scarce domain expertise and how this bottleneck shapes the economics of industrial AI training data.
You can't train a reliable model on data from an unverified source. By assigning every industrial sensor a unique distributed identity, Assay creates a cryptographic audit trail from the machine to the marketplace.