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Continual AI for modern data teams
Continual is an AI platform that simplifies predictive model building on modern cloud data platforms. It eliminates the need for complex engineering or MLOPS platforms and offers compatibility with popular cloud data platforms like BigQuery, Snowflake, Redshift, and Databricks. Continual improves models over time, stores data and models directly on the warehouse, and shares features across teams to accelerate model development. Use cases include predicting customer churn, forecasting inventory demand, and estimating customer lifetime value. Designed for modern data teams, Continual is accessible to SQL, dbt enthusiasts, and data scientists integrating Python.Features:
- Compatibility with popular cloud data platforms
- Simplified process without complex engineering or MLOPS platforms
- Accelerated model development by sharing features across teams
- Continual improvement of models
- Direct storage of data and models on the warehouse
- Predicting customer churn, forecasting inventory demand, and estimating customer lifetime value
- Accessible to SQL, dbt enthusiasts, and data scientists integrating Python
- Zero infrastructure and easy consumption by BI and operational tools
