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AI and data solutions for a premium TV network

A premium US television network reaching 28 million American households works with AgileEngine on business-critical data systems and experimental AI features. Our Data Studio experts modernized the company’s data pipelines, introducing automation and standardization to core data engineering workflows. Thanks to our AI team, the company was able to rapidly develop proof-of-concept AI-driven MarTech while saving engineering costs.

Industries

Digital media, Entertainment, Subscription

Services

Data engineering, AI engineering

Solutions

AI, Predictive analytics, Churn prediction, Data pipelines

Technologies

Python, SQL, AWS Sagemaker, AWS Batch, AWS ECS, AWS EMR, XGBoost, Bash, Airflow, Snowflake, Tableau

Outcomes
and highlights

  • 95% projected accuracy demonstrating that AI-driven churn prediction can significantly outperform traditional methods
  • Up to 5X potential cost-savings unlocked through improved retention compared to the average cost of acquiring new subscribers

Solutions overview

AI solutions overview AI-driven churn detection

AgileEngine’s AI Studio led the development of a PoC enabling AI-driven churn detection based on gradient boosting. This solution allows product teams to define user cohorts with greater accuracy by predicting the likelihood of subscribers leaving the platform. The PoC demonstrated how AI could enhance retention strategies and move beyond heuristic-based decision-making.

Key deliverables

  • Churn forecasting PoC using predictive AI (gradient boosting and logistic regression) to analyze historical data and estimate churn probability
  • Batch processing for AI/ML model training and analysis
  • Automated monitoring of AI predictions which enables prevention of issues like bias, hallucinations, model drift, etc.

Technologies

  • Python, SQL, AWS Sagemaker, AWS Batch, AWS ECS, AWS EMR, XGBoost, Bash, Airflow, Snowflake, Tableau

Data pipeline modernization

Our Data Studio experts’ work had a profound impact on the engineering workflows related to our client’s migration to a new technology stack. The version control and a standardized process introduced by our team streamlined the client’s data engineering pipelines, eliminating manual tasks and speeding up the detection and resolution of issues. With smarter automation in place, the company has seen significant improvements in data engineering speed and solutions reliability.

Key deliverables

  • Development of a robust and reliable data engineering solution for the client’s analytics teams
  • Migration of critical data pipelines to a new technology stack and architecture
  • Introduction of version control for the analytics projects, migrating and optimizing the data pipelines
  • Automation of end-to-end processes that include extraction from external data sources and execution of ad hoc Python scripts as batch jobs

Technologies

  • Python, SQL, Bash, Airflow, AWS Batch, AWS ECS, AWS EMR, Snowflake, Tableau

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