Edgewise stops data breaches and protects applications in hybrid clouds using patented zero trust technology driven by machine learning.

One of the biggest unsolved problems in cybersecurity today are flat, unprotected networks inside cloud and data centers. Flat networks allow attackers to move laterally with ease to compromise applications and cause data breaches. Traditional perimeter protection products, e.g., firewalls, cannot stop lateral threat movement inside the network, and are complex to operate.

There is a better approach -- Edgewise "Zero Trust Auto-Segmentation." Edgewise delivers impossibly simple microsegmentation that delivers results immediately, with a security outcome that’s provable. Edgewise uses patented Zero Trust Identity technology that allows applications to communicate only after their software identity has been verified. Malicious or unapproved software is no longer allowed to communicate. Lateral threat movement is stopped. Edgewise’s identity-based protection provides more coverage with fewer policies making it simple to deploy and manage. Edgewise machine learning simplifies operations further by automating policies. No changes to the application or the network are required. Edgewise protects any environment including bare-metal systems, virtual machines and containers, in the cloud and on premises.

Edgewise, a Gartner Cool Vendor and SINET 16 Innovator, has three approved patents and eight pending. Edgewise customers are in a variety of industries including Fortune 500 financial services, telecommunications, technology, and Ivy League universities.

Tulip's no-code manufacturing app platform, digitally transforms shop floors by giving real-time visibility into the people, machines and processes involved in production.

Manufacturers of all sizes, across industries including consumer electronics, aerospace and defense, contract manufacturing, automotive, apparel, medical devices and more, have implemented Tulip's intuitive platform to solve some of the most pressing challenges in manufacturing: digitizing paper-based processes, integrating industrial IoT (IIoT) technologies with legacy factory machines, and capturing and analyzing real-time production floor data.