3: Image metadata enrichment (race info)

Pain: It took us so much time and manual effort to identify and tag incoming images from sports events that we could only afford to do this in real time for a few of the most important events each year.  Even when being prepared in advance it was a slow and inefficient process that required a huge effort.  Because of this, our image metadata was minimal at best for all but the top-tier events meaning we were missing out on a lot of the long tail of value of both our current image inflow and our historical image repositories.

‍Pill: MediaHub integration with best-in-class AI image recognition from AWS to provide seamless metadata enrichment of both real-time and archived images and assets.

Description: Using MediaHub’s ability to seamlessly integrate best in class AI micro services into both real-time and on-demand digital workflows.

Proof: By using MediaHub’s ability to integrate AWS’s AI micro services into our real-time and on-demand digital workflows we are now able to consistently publish top-tier events faster with high quality and lower costs than ever before.  We are also now delivering expanded coverage of local and regional events which we believe is reducing churn and strengthening connections with our subscriber base.

MediaDropBox -> Openstore -> MediaHub -> ImageAnalyse -> MediaHub -> RaceInfo -> MediaHub -> Openstore

Keywords: Openstore, MediaHub, MediaDropBox, Chain of events, AWS Rekognition Image, Google GCP
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