Continual is an operational AI platform designed to simplify predictive model building on modern data stacks. Key features and advantages include:

• Compatibility: Works with popular cloud data platforms like BigQuery, Snowflake, Redshift, and Databricks
• Simplified process: No need for complex engineering or MLOPS platforms, build models using SQL or dbt declarations
• Shared features: Accelerate model development by sharing features across teams
• Continual improvement: Models improve over time, ensuring up-to-date predictions
• Direct storage: Data and models stored directly on the warehouse for easy access with operational and BI tools

Use cases for Continual cater to various business needs:

• Predict customer churn to improve retention strategies
• Forecast inventory demand for efficient supply chain management
• Estimate customer lifetime value to optimize marketing efforts

Designed for modern data teams, Continual is accessible to both SQL and dbt enthusiasts as well as data scientists integrating Python.