Egress specializes in AI-driven data privacy and compliance software that secures unstructured data, one of the hottest growth areas in an industry faced with growing concerns about the security of online information. Egress recently collared $40 million in a Series C Funding round led by FTV Capital and AlbionVC.
More on Egress from this report in BusinessWire:
A market leader in privacy and risk management, Egress helps enterprises protect unstructured data to meet compliance requirements and drive business productivity. The company’s AI-powered platform enables users to control and secure the data they share in line with evolving compliance regulations, including GDPR, the NYDFS Cybersecurity Regulation (23 NYCRR 500), and the recently-passed California Consumer Privacy Act. Since raising $3.6 million in Series A funding in February 2014, Egress has grown ARR by 9x, acquired over 2,000 customers and now supports more than five million users globally.
Egress customer, the State of Delaware, has been using the technology to help protect highly sensitive data and manage compliance. “As a regulated US Government State Agency, we recognized the importance of selecting a best-of-breed security partner,” explained Director of Network Engineering Mark Cabry. “Egress understands our complex business requirements and their technical innovation has helped us to maintain privacy and mitigate risk when sharing data across and outside government, leading us to deploy the service state-wide. It is therefore of little surprise that Egress is continuing to gain significant traction throughout the US market.”
Tony Pepper, CEO and co-founder of Egress, commented on the announcement: “Today’s heightened security threats, combined with an increasingly complex regulatory landscape, means that organizations face considerable risk from data breaches, resulting in reputational damage and significant financial loss. At Egress, we help businesses mitigate this risk by wrapping security around the user and managing their experience using machine learning and AI. This risk-based approach helps users avoid potential mistakes, such as sending information to the wrong recipients, and provides security administrators with insight into behavioral anomalies across the business.”
