The operational AI platform for the modern data stack

Continual is the easiest way to build and maintain production ML models – from customer churn to inventory forecasts – directly on top of Snowflake, BigQuery, Redshift, and Databricks.

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Empower everybody to leverage AI

Data First

Put data first where it belongs

Automated

Embrace a declarative AI workflow

Operational

Be ready for day 2 operations

Leverage your existing cloud data platform

Eliminate data and analytic silos by building on the data foundation you already have.

Integrate directly with Snowflake, Redshift, BigQuery, and Databricks

Leverage all your production data without costly integration efforts

Get predictions immediately in your existing BI and operational tools

Define and share features across your use cases

Accelerate model development with a shared feature store and data-first workflow.

Leverage SQL and your data warehouse for feature engineering

Prevent data leakage with support for feature time travel

Join relational and temporal features automatically into models

Declaratively manage your predictive models

Deliver new use cases in a fraction of the time without writing more ML pipelines.

Build and deploy models 10x faster with a declarative workflow

Get state-of-the-art performance with fully automated model training

Bring your own models and extend Continual to work without limits

Get continually improving predictions at scale

Maintain and monitor your predictive models without pipeline jungles or complex engineering.

Automate model retraining, promotion, and rescoring

Consume historical and current predictions in your data warehouse

Gain full visibility into the performance of models over time

A next-generation MLOps platform you can fall in love with

The power and flexibility you need with none of the complexity.

Team Collaboration

Collaborate with your team in a shared workspace with fine-grained access control.

Audit Logs

Track changes and audit the full history of feature, model and prediction model updates.

Feature Time Travel

Avoid feature leakage with point-in-time correct features and automatic temporal joins.

Continual Improvement

Keep predictions up-to-date efficiently using either incremental or full refresh policies.

End-to-End Monitoring

Monitor performance over time to avoid data drift and costly prediction errors.

CLI/SDK and dbt Support

Build models from the UI or drive your production models directly from a CLI/SDK or dbt.

Drive business impact from AI in minutes not months

Continual empowers analytics and AI teams teams to deliver continually improving ML models without complex engineering.

See how Continual can help you solve your use cases