Media & Entertainment

IDenTV operates on the front lines of applied AI in the M&E industry, creating rich metadata for workflow optimizations and big video data search, providing tools that code faces, brands, and logos, and that allow for the creation of custom AI models within hours. IDenTV’s solutions enable your business users to leverage the power of AI to automatically search petabytes of live or archival video. Further, by introducing real-time video analytics, multilingual media monitoring, and contextually matched personalized content, IDenTV’s solutions empower our partners in the M&E industry to maximize the value of applied AI and video analytics, increase engagement content, facilitate search and actionability within big video data, optimize workflows, and become data-driven in their decision making processes.

Live Events

IDenTV’s easy to use tools generate real-time analytics on big video content from broadcast, to OTT, VOD and more. IDenTV’s advanced AI platform allows our partners to extract actionable analytics on brand sponsorships from live sporting events in real time, a far cry from the error- prone, inactionable, and slow-moving report system currently in place. IDenTV’s advanced computer vision enables optimization of sponsorship placements to ensure your brand receives more on-screen time. Moreover, by providing actionable insights into big video data, IDenTV allows our partners to utilize these metrics to formulate a more accurate ROI! Finally, leverage IDenTV’s suite of vision, audio and NLP engines for a proactive solution that address public safety, traffic and congestion, and much more.

Retail Analytics

Utilizing existing security cameras, most often live streaming CCTV feeds and/or forensic analysis of video archives (recordings), IDenTV generates a customizable in-store retail experience.

Without violating personal privacy, IDenTV’s suite of AI and Machine Learning solutions enable partners to extract from CCTV streams key insights such as:

  • Branch traffic, providing more accurate counting filtering out employee activity
  • Unique consumer in-store path tracking and heatmap generation
  • Demographic data extraction to identify more tailored experiences
  • Queue analytics to lower wait times and operational excellence
  • Teller efficiency analysis and anomalous activity recognition and alerts
  • Along with advanced security applications such as blacklist facial recognition of persons of interest to alert security and deploy resources to remove bad actors from branches.

IDenTV helps its partners to better understand and correlate unstructured and structured Point of Sale data with the video analytics gathered via computer vision powered AI engines. Allowing for applications to customize in-store experiences but also creating robust decision support tools for leadership with macro and micro level analytics that help identify peak in-store traffic times, recognize operationally efficient or inefficient branches for calculating branch performance scores to assist in determining investment or divestment of specific locations. Further, provide unparalleled insights for not only improving the customer’s experience in being able to identify and cluster consumers and drive recommendations of specific products based on analysis of historical partner data and current inventory to optimize the interactions with the sales associates who will now be equipped with intelligence to further tailor the experience.

This solution is designed with ease of use in mind, where non-technical users can leverage and even augment/customize existing engines to continuously evolve with the consumers shifting tastes and industry trends. Facilitating workforce augmentation and automation without requiring large capital expenditures or expecting our partner to have an expansive internal data science team, thus not only creating analytics for tailored in-store experiences to thickening existing revenue streams, but decision support tools that can scale to save a large amount of time and money while respecting privacy. All facilitating a feedback loop for continued innovation to meet the evolving demands of consumer expectations from an in-store shopping experience.

Unlike many submissions we are already working closely with cloud partners such as Oracle Cloud’s GPU infrastructure to be able to power these types of capabilities for large retailers, banks and quick service restaurants around the world. In doing so we can create an immediate take-away in providing easy access via cloud partners to automatically launch demo instances for our partners to start testing and evaluating these solutions and expand the use-cases from those listed above.