Dizz Data

Dizz Data is AI-driven solution for design optimization and data analyt...


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Dizz Data is an AI-driven platform solution that provides design optimization and predictive analytics. Based around deep learning models, the platform generates new designs and evaluates existing designs for predictive modeling. This automated process reduces time and labor while simultaneously solving the need for accurate data science.

Key Highlights:

  • Active proprietary model for predicting player churn, lapse and fraud in gaming industry
  • Provisional patent filing is underway for design validation & generation using deep learning models
  • Moonfrog Labs, India’s largest gaming company, is a Dizz Data client

Business content is currently generated by hired designers. The design team must brainstorm and evaluate each new template, which is both labor intensive and time consuming.

Additionally, the data science team depends on expensive data scientists to analyze the success of previous content and develop predictive models. Acquiring a reliable third party service or in-house team member is a very difficult process.

The Dizz Data platform solution simplifies the design and predictive modeling process through AI-driven and deep learning software.

Businesses can upload images to the platform and automatically generate new designs or validate current design structures.

The platform also offers automated predictive modeling based on uploaded data and features. The user can then improve models through accuracy metrics and feature selection algorithms.

Streamlining the design and machine learning process requires coverage from creation to analytics. The Dizz Data platform provides a comprehensive solution in three core features:

The DizzData core features are showcased through our AI-driven gaming solutions:

  • Player Lifecycle Tracking predicts usage drop, lapse, and churn
  • Cheater Identification without manual intervention for those outside the rule structure
  • Player Segmentation and Feature Testing to better understand users

  • Matchmaking for competitive and collaborative player features
  • Experiment Balancing through multiple tests and validations with same user
  • Tuning and Validation powered by AI tracking and revenue correlation

  • Chat-bot Development for in-game player support and guided progression
  • Asset and Level Generation reduces game design time

The AI-driven results of Dizz Data are already attracting
the attention of industry leaders.

Moonfrog Labs, India’s largest gaming company, has agreed to purchase the DIZZ DATA predictive model solution for player fraud and collusion in the gaming industry.

Additionally, provisional patent filing is underway for design generation and validation process. Other algorithms are also subject for potential patents.

Chandra Shekar Prasad - CEO
Chandra has been working in data science and advanced analytics for nearly 11 years. As the former head of Data Science and Analytics at Zynga
he recognized the usefulness of AI techniques in identifying player churn and revenue softness and sought to apply those techniques to other industries. He is a 2006 graduate of the Indian Institute of Technology Delhi.

Amar Kumar Dani - CTO
Amar has been specializing in data science and machine learning for the past 8 years. He previously worked alongside Chandra as a Senior Data Scientist at Zynga before helping identify the AI techniques that would become Dizz Data. He graduated from the Indian Institute of Technology Kharagpur before receiving his Masters from Carnegie Mellon University in 2011.

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