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Cinemagic.AI is a system that can predict movie success, measured by return on investment. It uses various factors to provide a detailed breakdown and evaluation of potential future success.

Cinemagic.AI will make for better investment decisions in the long term.

It seeks to reduce a level of uncertainty, resulting in more informed investment decisions.

Unfortunately, human mind is not able to comprehend the entirety of the world, with its analytical data and relationships to take into account; that’s the job for a machine.

Many people trust their gut, honed through years of experience; this gut feeling guides their decisions. We try to find a pattern in random events, which leads us further away from the right decision.

AL and ML in the movie industry and stock market prediction are cut from virtually the same cloth: you need to identify trends and patterns based on empirical data.

The movie industry is something that has a set of features we can use to look for patterns which have a close connection to reality.

How do we reach it?

Stage 1 (research)
Status: completed
  1. Do research and collect all models we can possibly find that might carry the day
  2. Test those models and identify the best-performing parameters
  3. Write an effective case study which proves that the algorithm actually works
Stage 2 (application)
Status: WIP
  1. Research into the ways we can leverage models for new formats, languages and data sources
  2. Build an MVP to launch it and map out our product offer
  3. Use MVP to discover a viable monetization strategy and development model

Research result

Research requirements

Research process

Research result

  1. We designed a neural network to build a model, which will help predict the box-office receipts of a particular feature movie
  2. To evaluate financial performance of a movie, the classifier uses the following formula of return on investment (ROI):
  1. Analytically-wise, the classifier builds on six key metrics:


A neural network responsible for modelling box office prediction was designed

Key indicator

Our key indicator estimates project success by ROI:

where A is a target parameter

Classifier model

Analyticial model of the classifier is based on 5 key indicators:

  1. Quantitive indicators: budget, box office
  2. Categorical indicators: movie genre and tags
  3. Rating indicators: IMDb and other sources' ratigns
  4. Text indicators: title, slogan, synopsis
  5. Graph indicator: connections between actors and other movie makers
  6. News indicators: emotional estimation of text and titles relevant to the movie

Classifier Results

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