Continual, an San Francisco, CA-based next-generation AI platform for the modern data stack, has announced that it raised $14.5 million in Series A funding and general availability of its cloud platform.
This follows on the company's announcement of its public beta and partnerships with Snowflake and dbt Labs. While we have lots still in store, we encourage everyone to sign up for a free trial or request a demo to experience Continual for yourself.
Continual is an operational AI platform for the modern data stack. Continual enables data teams to build continually-improving predictive models — from customer churn to inventory forecasts — directly on top of cloud data platforms like Snowflake, BigQuery, Redshift, and Databricks. Unlike traditional MLOps platforms, Continual is powered by a declarative design and end-to-end automation. There’s no complex engineering or operational burden.
Continual after a decade of working on traditional MLOps platforms and being frustrated with the results. While today’s leading enterprises are increasingly AI-driven, operational AI is drowning in complexity. Production machine learning platforms bear a striking resemblance to the early days of “Big Data”, where writing map-reduce jobs was required to answer simple analytical queries. Even for the simplest use cases, putting models into production requires complex infrastructure, bespoke pipeline jungles, and never ending operational babysitting. It’s costly, slow, and just no fun.
Over the last decade, data platforms have undergone a profound transformation driven by the rise of cloud data platforms like Snowflake, BigQuery, Redshift and Databricks. These platforms have struck at the heart of Big Data complexity and rightfully become the center of gravity for modern data architectures. Building upon this new potential, a vibrant modern data stack ecosystem has emerged spanning data ingestion, transformation, and activation. These modern data stack tools deliver best-of-breed solutions to common parts of the data lifecycle.
Continual brings this same ethos of radical simplicity to operational AI. It sits directly on top of cloud data platforms and enables anyone to build and maintain predictive models that never stop learning from their data. With Continual, putting a predictive use case into production, including model maintenance and monitoring, requires no custom pipelines or infrastructure. Whether you’re an analytics engineer or data scientist, you can focus on what matters most — delivering business impact.
