Continual is an operational AI platform designed to simplify predictive model building on modern data stacks. Key features and advantages include:
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Compatibility: Works with popular cloud data platforms like BigQuery, Snowflake, Redshift, and Databricks
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Simplified process: No need for complex engineering or MLOPS platforms, build models using SQL or dbt declarations
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Shared features: Accelerate model development by sharing features across teams
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Continual improvement: Models improve over time, ensuring up-to-date predictions
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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:
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Predict customer churn to improve retention strategies
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Forecast inventory demand for efficient supply chain management
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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.
