Continual, a startup looking to bring operational AI to the modern data warehouse-centric data stack, today announced that it has raised a $4 million starting round led by Amplify Partners, with Illuminate Ventures, Essence, Wayfinder and Data Community Fund also participating. the round. With this announcement, Continual is also opening up its service as a public beta, after testing it with select customers over the past few months.
The data warehousing space is huge, but it is also dominated by a small number of players, such as Snowflake, Amazon Redshift, BigQuery and Databricks. This makes it easier for startups that want to use the data stored in it to build their own innovations. For Continual, that means providing companies with an accessible tool to build predictive models.
“[Continual] enables modern data teams to build and maintain continuously improving models right on top of their data warehouse,” explains Tristan Zajonc, CEO and co-founder of Continual. “The common use cases we see are things like customer churn, lead scoring, product recommendations, inventory forecasting, predictive maintenance, service, automation, etc. Essentially, continuously maintains both the predictive model and forecast. Using data from the data warehouse and writing the predictions back into the data warehouse.”
Zajonc’s latest startup, Sense, was an early enterprise platform acquired by Cloudera in 2016, while its co-founder, Tyler Kohn, previously built RichRelevance, a personalization service acquired by Manthan System in 2019. two co-founders noted the high failure rate for AI projects in the enterprise. Usually, a large team and a lot of resources are needed to execute these projects, while the required AI infrastructure is becoming more and more complex.
“We’re moving from this era of big data to this era of great complexity,” Zajonc said. “We founded Continual to solve this problem and radically simplify operational AI for enterprises. We realized that the rise of cloud data warehouses – the standardization of data infrastructure and the emergence of the modern data stack in general – gave us the opportunity to rethink and radically simplify enterprise AI.”
With Continual, data teams can reuse their existing SQL and dbt skills. All they have to do is connect Continual to their data warehouses and then define declaratively which features and models they want to predict. A handy feature here is that the predictions are also stored in the data warehouse, where they are directly accessible to developers and analysts if necessary.
The platform currently supports Snowflake, Redshift, BigQuery and Databricks and the team plans to expand its partnership with dbt and these data platforms over time. However, as Zajonc pointed out, the company has no interest in becoming a data integration platform.
“Continually improving predictive insights from data is critical for businesses to operate efficiently and better serve their customers. Still, operationalizing AI remains a challenge for all but the most advanced companies,” said David Beyer of Amplify Partners. “Continual meets data teams where they work – in the cloud data warehouse – and lets them build and deploy continuously improving predictive models in a fraction of the time existing approaches require. We invested because we believe their approach is fundamentally new and, most importantly, the right one is to make AI work across the enterprise.”
The company plans to use the investment to double its team over the next year and expand its platform to support natural language processing, personalization and real-time use cases.