Crafted to work natively with modern cloud data platforms
Connect to your existing cloud data warehouse and leverage all your data where it already lives.
Share features and deploy state-of-the-art ML models with nothing but SQL or dbt or extend with Python.
Maintain predictions directly in your data warehouse for easy consumption by your BI and operational tools.
Maintain features and predictions directly in your data warehouse without new infrastructure.
Share feature definitions defined in SQL across your team to accelerate model development.
Build state-of-the-art models that leverage all your data without writing code or pipelines.
Leverage your existing dbt models and workflow to radically reduce the complexity of operational AI.
Govern features, models, and policies with a declarative GitOps workflow as you scale.
Unite analytics and AI teams with full extensibility of Continual's declarative AI engine.
“dbt was built on the idea that the unlock for data teams is a collaborative workflow that brings more people into the knowledge creation process. Continual brings this same viewpoint to machine learning, adding new capabilities to the analytics engineers' tool belt. We’re excited to partner with Continual to help bring operational AI to the dbt community.”
“Continual is enabling organizations to easily build, deploy, and maintain continually improving predictive models directly on top of Snowflake. As part of our partnership, we’re excited to help bring these benefits to the Snowflake community and to accelerate end-to-end machine learning workflows on top of Snowflake with Snowpark.”
“Continual gives data and analytics teams the power to build and operationalize predictive models in a fraction of the time. By putting the data warehouse at the center, Continual radically simplifies enterprise AI.”