The ClumL AI Clustering Engine is a high-performance, unsupervised learning–based clustering engine, protected by a U.S. patent, and serves as the core intelligence of autonomous security, capable of capturing not only threat signals but also their progression and flow.
Developed jointly by ClumL’s research teams in the U.S. and Korea, this engine is built on ClumL’s accumulated proprietary technology and serves as a key competitive advantage in the global market.
Principle and Structure
The engine identifies multi-dimensional behavioral patterns in unstructured raw data in real time, autonomously grouping data by similarity and pattern without predefined rules.
This makes it capable of detecting previously unknown anomalies and irregular behaviors, with a special design focus on capturing the flow and context of network threats.
Through high-performance Incremental Clustering, which can immediately incorporate real-time data updates, the engine ensures greater analytical accuracy and rapid detection of the latest threats.
Clumit’s Incremental Clustering
Differentiation: Clumit Incremental Clustering vs. Other AI Security Solutions
Real-Time Large-Scale Data Clustering
Analyzes both structured and unstructured data at backbone-level traffic scale
Captures the entire flow of malicious activities in real tim
Abnormal Behavior Detection
Mirrors the entire network to detect abnormal communications such as suspicious domain connections or unusual data exfiltration at irregular times
Context-Aware Threat Detection
Learns normal behaviors per device/network, clustering across time-series changes
Detects threats in evolving contexts, enabling the most advanced form of autonomous security
Expandable Raw Data Analysis Scope
Goes beyond real-time traffic to include diverse activity logs from endpoints and servers
Enables expanded clustering models tailored to specific detection objectives