Multi-dimensional metadata trained and structured from public data.
TL;DR
It all begins with data. CoTensor uses proprietary NLP extraction engines to structure, reconcile and gapfill metadata from any publicly available reference source.
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Ontological Precision
CoTensor has outperformed reference authorities on evaluation metrics such as completeness, refresh rates, accuracy and precision; CoTensor is capable of inbuing structure to sparse matrices / tensors and all data shapes.
Synthetic Metadata
CoTensor pioneered the practice of generating synthetic metadata based on training data in order to overcome cold-starts on new entity generation.
Engage
CoTensor licenses AI-generated knowledge based data-sets with multi-dimensional metadata for select clients. Licenses include complete ownership of enriched graph, including all indexed and synthetically generated attributing.