On August 5, 2021, InsightFinder was honored to receive the National Science Foundation Small Business Innovation and Research Phase I award (aka America’s Seed Fund). This funding recognizes InsightFinder’s quest to further innovation in the IT operation space and supports InsightFinder’s research and development in self-learning incident auto-remediation. InsightFinder will develop intelligent learning techniques to automatically infer remediation actions without requiring tedious and error-prone human interactions. This project will also support the company to build the first enterprise-grade active learning system that is always improving based on constant system health monitoring and user feedback.
The overarching goal of the investment in InsightFinder’s research is to improve the assurance and durability of enterprise IT infrastructures. As companies become increasingly dependent on digital technologies, it is crucial that businesses can consistently stay online through their foundational infrastructure. InsightFinder’s research will focus on the following: 1. building universal pattern extraction themes from various sources, including log data, complex incident ticket data, and metric data 2. exploring self-healing remediation system that can recommend proper remediation by looking at incident and root cause patterns, and 3. constructing an easy to use remediation workflow engine that allows users to trigger different workflows to prevent incidents in one place.
InsightFinder is the leading AI technology for IT infrastructure, using patented unsupervised machine learning to predict and prevent IT incidents and automate root cause analysis. InsightFinder is unique because it leverages machine data across data types, and addresses the curse of dimensionality. Established in 2015 by NC State professor Dr. Helen Gu, InsightFinder currently has customers including Dell, Credit Suisse, and China Mobile.