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Cinelytic Extends Big Data And Predictive Analytics To The Entire Film Industry

 

Cinelytic, a New York and Los Angeles based tech startup, today announced that it will launch its revolutionary online big data and predictive analytics platform for the film industry at Cannes this year. Cinelytic offers a comprehensive online system that provides the global film industry with data-driven decision support tools for all phases in a film’s life cycle, including packaging, financing, production, distribution and marketing. The Cinelytic system includes comparative, as well as highly sophisticated predictive technology to promote greater transparency and efficiency, as well as better business practices and smarter decision-making in the film space.

Cinelytic’s online platform is an industry first, providing a single, integrated decision support system for the entire film industry, including production companies, distributors, sales agents, financiers and studios. The system includes sophisticated film and talent comping tools, project packaging analytics, fully integrated financial planning tools, as well as a predictive forecasting tool for all film revenues (US and international theatrical, VOD, DVD, and TV) for projects from the development stage forward. Cinelytic combines a broad range of data sources including P2P piracy downloads, financial release data and social media tracking. The system also integrates various decision and valuation metrics, as well as visualizations to provide users with deeper insights.

“Cinelytic provides clients with an unparalleled understanding of the value and characteristics of filmed content before it has been produced. Utilising the increasing amount of available data, together with our proprietary machine learning algorithms, Cinelytic provides producers, financiers, distributors and studios with game-changing insights to help get projects made, and to decrease financial risk,” states Tobias Queisser, co-founder.

This article was originally publshed on www.fox34.com and can be viewed in full

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