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Price: 500000

Number of applications: 15

Development of an AI system for personalized recommendations of video content for a digital media platform.
Customer

Azimut Tech
Decision acceptance deadline

26.06.26 (inclusive)

Form of award

Internal grant from the school

Product status

Idea

Task type

ICT tasks

Сфера применения

Media sphere

Область задачи

Neurotechnology and artificial Intelligence

Type of product

The website

Problem description

With the rapid growth in digital video content consumption and the increasing number of users of streaming platforms, media companies are facing the challenge of content personalization and audience retention. With a large volume of video materials, it becomes more difficult for users to quickly find relevant content, which reduces engagement and negatively affects audience retention rates. Existing recommendation algorithms do not always take into account user preferences in real time, and manual analysis of audience behavior requires significant time resources. This limits the ability to scale media platforms and reduces the effectiveness of user interaction.

Expected effect

After the implementation of the solution, it is planned to create an intelligent recommendation system based on artificial intelligence technologies that will analyze user behavior, browsing history, preferences and audience engagement. It is expected to increase user retention time within the platform, increase the number of content views, increase audience engagement, improve user experience, and increase the efficiency of the platform through personalized content delivery.

Full name of responsible person

Bolotbekov Alisher Rustambekovich

Purpose and description of task (project)

Development of an AI system for personalized recommendations of video content for a digital media platform. The solution should provide real-time analysis of user behavior, take into account browsing history, interaction with content, genre preferences, and automatically generate a personalized recommendation feed. The system should use machine learning algorithms for continuous self-learning based on new user data, as well as provide the ability to analyze the effectiveness of recommendations and the impact on user activity. The main goal of the project is to increase user retention, increase audience engagement, and optimize content delivery processes through the use of artificial intelligence technologies.

Note

The company is interested in working with Backend developers, Data Engineers, AI/ML Engineers, and teams with experience in developing recommendation systems, high-load video platforms, and user behavior analysis systems.

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