GumGum Launches Verity Contextual Analysis for Digital Publishers

GumGum, a technology and artificial intelligence company for advertising and media, has released Verity, a content classification and brand safety solution that analyzes the full publisher content of web pages, including images.

Built around GumGum's proprietary computer vision and natural language processing deep learning systems, Verity offers content-level insight into ad inventories by expanding available contextual categories and identifying brand suitability and safety concerns.

"Looking ahead to a cookieless future, we saw that publishers would need greater insights about their content to facilitate the potent, safe, contextual targeting experiences that will drive revenue," said GumGum's CEO, Phil Schraeder, in a statement. "Those insights can't come from basic text and metadata search, because the web is visual. You need to see the pages the way users do if you really want to understand what they're about. With Verity, we're giving you the whole picture so you can get the greatest value out of your content."

Verity features machine learning for keyword, named entity, object, and hate logo detection, as well as contextual taxonomy, major event, scene, threat, and sentiment classification. Sentiment analysis algorithms allow Verity to capture attitudes, opinions, and emotions expressed online.

"Verity is a consummation of 10-plus years developing leading-edge machine learning expertise for content analysis," Schraeder said. "We're pleased to be sharing that expertise with publishers now...when contextual targeting and brand safety are becoming absolutely vital to the health and survival of the online publishing ecosystem."

Verity's lightweight API integrates with all traditional content and data management platforms.