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arXiv · 2610.30518

Protegrity-PII Technical Report

Hardeep Bassi·Hui Ma·Luís Seabra·Koowum Joshi·Daniel Pereira·Averell Gatton
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Abstract

We present Protegrity-PII, a new PII decision model for structured and unstructured text. Protegrity-PII achieves a typed recall of 0.915 with a precision of 0.907 on a new benchmark we propose, PII-SCOPE. Our model processes text in 0.49 seconds per million characters at \$0.0005 per million characters on a single RTX 6000 using batched inference. Due in part to the expansive nature of the entity type taxonomy used in training, Protegrity-PII achieves superior out-of-distribution generalization when benchmarked against a selection of state of the art models and datasets.

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Hardeep Bassi, Hui Ma, Luís Seabra, Koowum Joshi, Daniel Pereira, Averell Gatton. 2026-10-21. Protegrity-PII Technical Report. https://arxiv.org/abs/2610.30518

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