Nightfall heralds dawn of first AI-powered file classifiers
Spookily-named AI-native data loss prevention platform company Nightfall has now detailed the shape of its new ‘AI File Classifier Detectors’, a software service deisgned to use large language models (LLMs) to classify and protect business-critical documents that traditional DLP tools cannot see
DLP tools?
Yes, data loss prevention tools i.e. cybersecurity services built to detect, monitors and protects sensitive data to prevent it from being leaked, misused, or lost.
Why are DLP tools so important?
Most high-value assets (including source code, financial reports, strategic roadmaps, patents and proprietary research) contain no traditional sensitive data identifiers…. So as a result, they are invisible to legacy pattern-matching tools.
Legacy pattern-matching tools?
Yes, archaic and outdated enterprise apps designed to identify specific patterns in data using rule-based rigid methods such as regular expressions and keywords that are defined as “static” because they have a hard time working with contemporary unstructured data and complex context… and so are prone to false positives or negatives.
Nightfall says that this blind spot exposes organisations to intellectual property theft, insider threats and accidental leaks through modern collaboration platforms and shadow AI tools.
The company claims to close this gap with LLM-powered document intelligence that goes beyond pattern matching or simple semantics.
Meaning, structure & context
Importantly, Nightfall’s classifiers understand document meaning, structure and business context i.e. the same cues humans use to recognise a contract, source code repository, or merger and acquisition plan.
The result is accurate detection of unstructured IP without reliance on brittle rules or manual tagging.
The solution provides coverage for 22 common document types and allows teams to build custom detectors using plain language prompts and example files, eliminating the need for regex patterns or large training sets.
“The most devastating data breaches aren’t credit card numbers or social security digits – they’re the theft of years of R&D, customer strategies, or source code that represents millions in competitive advantage,” said Rohan Sathe, CEO and co-founder of Nightfall. “Traditional DLP tools are blind to these assets because they’re designed for structured data, not business intelligence. Our AI File Classifiers finally give security teams the ability to protect what actually matters most: the unstructured intellectual property that drives business value and competitive differentiation.”
Users can define new business document types using a prompt-based file classifier. For example, a lender can upload a sanitised mortgage application or describe it as “a home loan form with borrower income, asset and liability fields” so that Nightfall’s AI learns the structure and context to automatically generate a tailored detector.
The company says that no custom rules, training data, or engineering effort required.
“Unlike legacy DLP, Nightfall’s classifiers are explainable and adaptable. Each detection includes confidence scoring and justification metadata, so teams understand why a file was flagged and can fine-tune policies to balance protection with productivity,” said Sathe. “With prebuilt protection for common document types and custom detectors for unique business assets, organisations gain both immediate value and long-term flexibility in a single platform that works across SaaS apps, endpoints and communication channels.”
The 22 prebuilt sensitive document types functionality means instant protection for legal contracts, financial reports, proprietary company-owned source code, product roadmaps, HR documents, M&A materials and other common business-critical file types.
Prompt-based file classifiers define new document types using natural language descriptions or example files – no “regex” or training data required.
Regex, defined
NOTE: Regex, or regular expression, is a sequence of characters used to define a search pattern for matching strings. It allows developers to search for, validate, or manipulate text based on specific patterns, which can range from simple to highly complex.
The technology here offers LLM-powered document intelligence: AI-powered analysis that understands document meaning, structure, and business context rather than relying solely on keywords or metadata patterns.
