SanoAI/sano-shield-1-multilingual

Sano Shield 1.1

Sano Shield 1.1 is Sano AI's multilingual privacy model for identifying sensitive information before text reaches an AI provider. Its technical model ID is sano-shield-1-multilingual.

Availability: This repository publishes the model card only. Model weights, tokenizer files, ONNX artifacts, and training data are not publicly distributed or downloadable from Hugging Face.

Model details

Field	Value
Model family	Sano Shield
Release	Sano Shield 1.1
Technical ID	sano-shield-1-multilingual
Task	Token classification / sensitive-entity recognition
Evaluated languages	German and English
Entity classes	35 entity types, 69 BIO token labels
Architecture	XLM-RoBERTa token classifier
Base-model lineage	bardsai/eu-pii-anonimization-multilang
Release date	2026-08-01

Sano Shield 1.1 continues a private Sano Shield 1.0 checkpoint. Sano Shield 1.0 was a full-parameter continued fine-tune of the pinned base-model revision 0e72e19f030ed4e661b1673e549af8e0dd176386. Training targets come from Sano's versioned synthetic corpus rather than predictions copied from a separate evaluator.

Intended use

Sano Shield 1.1 is designed as one component in a privacy pipeline:

1. identify sensitive spans in German and English text;
2. replace those spans with controlled placeholders before external model inference; and
3. support re-identification only inside a trusted boundary.

Production deployments should combine the model with deterministic recognizers, policy checks, monitoring, and fail-safe handling. Organization names remain user-selectable but are not treated as mandatory natural-person PII by the release policy.

The model should not be used as the sole basis for legal-compliance decisions, medical decisions, identity verification, employee monitoring, or irreversible actions affecting a person.

Evaluation

The promoted checkpoint passed both synthetic checkpoint gates and a separately maintained product-pipeline evaluation. The product evaluation data was held out from training.

Product gate	Sano Shield 1.1 result
German protected-span recall	470 / 470 (100%)
English protected-span recall	4,187 / 4,188 (99.976%)
Zero-touch documents	29 / 30
Raw false or unknown detections	83, reduced from 141
ONNX/PyTorch label agreement	100%

On the synthetic continuation evaluation, exact entity F1 improved by 0.0454 for German and 0.0209 for English relative to the Sano Shield 1.0 parent, while privacy-span recall was unchanged.

These results do not guarantee equivalent performance on other domains. The held-out product evaluation measures Sano's release policy and complete product pipeline, including deterministic rules; it should not be interpreted as a neural-model-only benchmark.

Training

• Parent: private Sano Shield 1.0 selected checkpoint
• Corpus: Sano Shield v0.4 synthetic continuation corpus
• Schedule: one epoch at a 1e-6 learning rate
• Composition: 62.5% replay, 25% positive contextual data, 4.2% contrastive data, and 8.3% new negatives
• Loss: square-root inverse class weighting capped at 3.0, with the outside label at weight 1.0

The continuation run restarted from Sano Shield 1.0 rather than from either rejected candidate run.

Limitations

• German and English are the only release-policy target languages.
• Unseen document types, OCR errors, adversarial formatting, and ambiguous context can produce missed or extra spans.
• No statistical detector can guarantee that all sensitive information is found.
• The model recognizes spans; it does not determine whether processing them is lawful or satisfy a particular compliance regime.
• High-risk deployments require domain-specific, legally usable, human-reviewed evaluation.

Distribution

This public page is provided for transparency about the model's purpose, lineage, evaluation, and limitations. It does not grant access to the checkpoint or corpus, and no public redistribution license for those artifacts is granted here. Contact Sano AI for deployment and access information.