Data Security Solution harnesses LLMs for Unstructured Data

Israeli firm Flow Security has designed a data security platform powered by Large Language Models (LLMs). With a focus on unstructured data, this technology can identify over 150 distinct data types with claims of unprecedented accuracy.

In an age in which companies generate data at an unprecedented rate, being able to classify sensitive data automatically has never been more urgent. This challenge is especially critical when dealing with unstructured data (e.g. free text).

Until recently, unstructured data was classified through traditional Named Entity Recognition (NER) algorithms, such as LSTM. Although they got the job done, these algorithms could only recognize a small set of data classes, were limited in accuracy and struggled with context. 

Now all this is changing with LLMs.

Over the past few months, Large Language Models (LLMs) have taken the digital domain by storm. Powered by vast and diverse datasets, LLMs can mimic and produce text with an uncanny resemblance to humans. What sets these models apart isn’t just their scale, but their natural ability to comprehend context, tone, and intent. 

Unlike traditional NER algorithms, LLMs recognize a wide range of data types and catch context that other models might miss. In addition, because they are trained on an overwhelming amount of data, their accuracy levels can reach that of humans and beyond. 

One of the biggest opportunities for LLMs to shine is unstructured data. Thanks to the capabilities mentioned above, LLMs can classify unstructured data with unmatched accuracy, flexibility, and scalability, leaving traditional methods far behind. 

Flow has incorporated LLMs into its classification technology. Its latest offering is bringing about a revolution in the understanding and classification of unstructured data. 

Designed with a strong emphasis on unstructured formats, Flow’s platform dives deep into free text and uncovers sensitive data. The engine identifies over 150 distinct data classes, including out-of-the-box classifications that align with industry benchmarks such as GDPR, HIPAA, CCPA, and PCI-DSS.

These can be further calibrated by users to suit their unique classification needs. Classification can be applied to anything from casual documents and detailed narratives to complex source code, audio files, images and videos (using OCR algorithms). 

Flow’s use of LLMs in data classification isn’t just powerful, it’s also extremely secure. The LLM-driven classification mechanism is located in the customer’s environment, which means that sensitive data remains entirely on-premises, and is not shared externally. In addition, the classification technology is designed for business continuity – optimized for performance and built for seamless integration and swift processing.


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