WitnessAI Unveils NER-D, a Breakthrough AI Model for Context-Aware Sensitive-Data Detection
New Model is 20x Faster Than Comparable Generative Methods While Delivering Benchmark-Leading Accuracy and No Trade-off Between Speed and Quality
NER-D enables AI the ability to understand the context behind words. In a live AI conversation, it can instantly distinguish whether the word "Paris" refers to a city (
The NER-D model introduces a paradigm shift: full-context semantic data protection at real-time speed. NER-D evaluates AI conversations the way a human reviewer would, identifying sensitive information by what the data means, not just its structure. By combining large language model (LLM) world knowledge with live production speed, NER-D can instantly comprehend the true context of an interaction, closing the contextual detection gap left by legacy solutions, securing the unstructured, never-before-seen concepts that existing tools were not designed to comprehend.
"WitnessAI's mission is to secure enterprise AI," said
Developed with significant contributions from WitnessAI researchers
- Benchmark-leading accuracy: NER-D achieves the highest accuracy of any benchmarked method, outperforming the previous industry best by 7.9 points. It delivers the most significant gains on complex data types where nuanced, contextual understanding matters most.
- Production-ready speed: By classifying in one parallel pass instead of generating answers token by token, NER-D operates over 20x faster than comparable generative methods.
- Robust world knowledge: Built on a full LLM, NER-D already understands global data formats and industry concepts like national ID formats, pharmaceutical compounds, and trading concepts. Enterprises can secure sensitive data simply by describing the concept, eliminating the need to manually list every possible variation.
- Significant reduction in false positives: NER-D reads the surrounding context of a conversation to understand true intent. This prevents the large volumes of benign alerts that can often arise when traditional tools misinterpret data. For example, flagging digits like a purchase order or invoice total as a sensitive identification number.
"Legacy tools match patterns, but NER-D understands the true meaning of AI conversations at live conversation speed," said
The NER-D capability will be available in the WitnessAI platform in the coming months. The model will feed directly into the data-protection workflows teams already run, such as redaction and tokenization.
To learn more about WitnessAI or to request a demo, please visit https://witness.ai/.
About WitnessAI
WitnessAI is the AI security platform enterprises trust to govern and protect all AI activity. We provide complete visibility into every interaction including employees and autonomous agents, even in native apps where legacy tools are blind. Unlike traditional security that relies on outdated keywords, our AI-native platform understands intent, context, and meaning enabling intelligent policies that stop novel threats like prompt injection while empowering productivity. Our enterprise-first, single-tenant architecture ensures data sovereignty and compliance. WitnessAI transforms security from a bottleneck into the enabler of your AI strategy as the confidence layer for enterprise AI.
Media Contact
Jessie Birkhofer
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SOURCE WitnessAI
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