The Role of AI/ML in Bolster Threat Assessment

Bolster integrates AI/ML technologies into the platform to optimize and automate the processes required to detect and monitor potential threats.

Search Algorithms

The search algorithms that drive the domain variant monitoring use AI to determine likely variants based on the domains you have registered with the platform. With a list of likely variants, the Bolster platform can prioritize domains for acquisition and monitor existing domains that have the potential to serve as scam hosts.

Computer Vision (CV)

Bolster’s image recognition algorithms detect brand hijacking in just a few milliseconds. Our computer vision models look through a page for all relevant objects (images, text, and images of text) to determine whether a brand is being infringed and the nature of the infringement.

Natural Language Processing (NLP)

Natural language processing models read through the displayed text and the site code to understand the intent of a site.

Deep Learning

The platform learns from proprietary datasets containing millions of image and text samples. Deep learning models combine the outputs from the NLP and CV models to classify and prioritize potential threats for mitigation.