CONTEXT CONNECT TM
TubeScan can analyze video content to identify the most attention-engaging time-points within your video which are higher engagement and less viewer-intrusive for advertising content insertion either in-stream or overlay. Tubescan combines well with ContextConnect making this advertising content incredibly relevant to the host content.
Video content is being created at a phenomenal rate and as internet connection speeds increase, video consumption increases logarithmically. Make sure your brand is taking advantage of this engaging medium.
IMAGE ASSURANCE TM
Objectionable Content Screening
As the environment that brand assets appear in becomes more fluid it becomes more challenging to guarantee brand safety. Additionally one brand manager may be happy with content that is not appropriate to another. ImageAssurance is able to facilitate automated brand safety against the requirements of the brand. Thus you are able to protect your brand against the following:
Nudity, drug abuse, weapons and violence.
Our solutions help you protect your brand against these or any other themes. For example: you may want to avoid advertising your product if nearby a image contains a certain competitor’s product or near news stories that may not be on-brand or category unfriendly.
We provide solutions to publishers with significant image and video content.
Content analysis when matched with the usual site visitor metrics, allows publishers to truly understand the consumer activity of their site. This helps evaluate content ROI but also helps the editorial process. Knowing which content is working and not working serves all advertisers and editorial staff alike.
GRAYMATICS COGNITIVE MEDIA ANALYTICS SOLUTION POWERED BY NVIDIA
Algorithms to power deep insights from images and videos are developed with Deep Learning neural network. NVIDIA GPUs are used to reduce the time it takes to process large datasets from weeks to few hours. Traditionally, CPUs are designed to deal with sequential instructions. On the other hand, GPUs are meant for handling multiple jobs in parallel with lower power consumption. GPU-powered deep learning has led to ground-breaking improvements across a variety of applications, including image classification, speech recognition, and natural language processing.