Continual offers a cloud platform that lets data teams build and deploy predictive models directly on top of existing data warehouses (e.g., Snowflake, Redshift) using familiar skills like SQL and dbt. The company focuses on predictive use cases such as inventory forecasts, risk mitigation, and supply chain logistics. Its service is not a low-code/no-code tool but emphasizes accessibility by enabling data teams to leverage existing workflows and tooling. Continual announced its platform is generally available after exiting beta and has a preview of extensible MLOps for custom models. The company plans to add automated feature engineering and later this year introduce real-time feature and model serving. In the last three months it doubled active users, deployed models, and booked annual recurring revenue. To support growth and product development, Continual plans to double its team by the end of 2022. Continual offers an AI-powered platform that lets data teams build and maintain predictive models directly on top of cloud data warehouses. The service integrates with Snowflake, Amazon Redshift, BigQuery and Databricks and stores predictions back in the warehouse for immediate access. Data teams can reuse existing SQL and dbt skills to declaratively define features and models. The company opened a public beta after testing with select customers. Continual raised a $4 million seed round to fund growth and plans to use the investment to double its team over the next year. The team plans to expand the platform to support natural language processing, personalization and real-time use cases; co-founders Tristan Zajonc and Tyler Kohn bring experience from startups that were acquired.

Total raised

$19M

Funding rounds

2

Latest round

Series A

Latest activity

Jun 2022