Make your data warehouse drive machine learning and AI

Continual is the missing AI layer for the modern data stack. Build continually improving predictive models – from customer churn to inventory forecasts – without engineering or operational burden.

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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 warehouse

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

Integrate directly with Snowflake, Redshift, BigQuery, and Azure

Leverage all your production data without costly integration efforts

Get predictions immediately in your existing BI and operational tools

Organize and share features across use cases with ease

Accelerate model development with shared feature management and a 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

Deliver production models in minutes not months

Leverage your teams existing SQL skills and a declarative workflow to get more done faster.

Build and deploy models 10x faster with a declarative workflow

Get state-of-the-art performance leveraging AutoML

Free up machine learning engineers for core product engineering

Get continually improving predictions to drive impact

Never worry about stale models or predictions with fully automated ML operations.

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

Powered by a data-first workflow and end-to-end automation

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 ML without the complexity

Continual empowers data teams teams to deliver production-grade ML models in minutes without more ML pipeline jungles.

See how Continual can help you solve your use cases