Rasgo Raises $25Million To Deliver The Feature Store For Cloud Native Databases And Introduce New Capabilities To The Data Science Community

Rasgo Intelligence, the feature store that is transforming how data scientists engineer, collaborate on, and operationalize Machine Learning (ML) features, announced a $20M Series A investment round led by Insight Partners, with continued support from Unusual Ventures. This brings Rasgo’s total funding to over $25M since its founding.

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Rasgo was founded by Jared Parker and Patrick Dougherty in 2020 to amplify the impact of data science by enabling end users to explore, clean, join, and transform data into highly curated ML features at 10x velocity.

In less than 12 months, Rasgo has accomplished the following:

• Global enterprise customers across finance, manufacturing, biotech, retail, and alternative energy
• Released PyRasgo, a free feature engineering experience to give back to the data science community which has already generated over 70,000 downloads
• Built a world class team across engineering and go-to-market across 3 office locations

“At AES, our mission is to accelerate the future of energy together, improving lives by delivering greener and smarter energy solutions helping everyone on a global scale take part in the evolution of energy. To accomplish this, we are leveraging Machine Learning and Artificial Intelligence across our energy businesses, but it is not a simple process.” said Sean Otto, Head of Data Science and Analytics at AES.  “To simplify, accelerate, and scale our AI and ML efforts, we are leveraging Rasgo to create and serve ML features as fast as we can think of them, reducing the time to designing unique and viable solutions from weeks to minutes.” Additionally, in the finance industry, Rasgo is being leveraged to accelerate predictions of financial instrument prices and market volatility. “Without Rasgo, we would have much difficulty tracking the predictive power of our features to quickly disseminate which trading strategies are delivering alpha,” said Christian Peressin, Manager at Chisholm Financial Labs, a leading algorithmic hedge fund; “with Rasgo, we can quickly serve and track features in our ML pipeline, which increases the velocity of our experiment and development loop and enables us to deploy new trading strategies faster.”

“In working with thousands of data scientists, we saw first-hand that data science projects continuously fail due to technical limitations and inefficiencies in the feature engineering process,” said Jared Parker, Rasgo founder and CEO. “Many ML projects never made it to production, and those that did were plagued with end user frustration due to the sheer time it took to clean, join, and transform data. At Rasgo, we are building a platform that enables data scientists to access and transform data into highly curated ML features in minutes, not weeks. Our early customers have eliminated the feature engineering bottleneck and are now creating more accurate features and models, which have allowed them to finally achieve tangible financial value from ML.”

Rasgo is also dedicated to accelerating adoption of the Data Cloud for data science and has developed an integration with Snowflake. “At Snowflake, we are continuing to build new capabilities for data scientists and data engineers,” said Snowflake Director of Technology Alliances, Tarik Dwiek. “Rasgo can help our customers use Snowflake to unlock net new use cases and develop high quality ML features that are ready for production. This can represent significant acceleration of ML projects.”

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Rasgo will use this funding round to accelerate product development, expand its team with a focus on engineering talent, and build out its go-to-market function.

“For most organizations, data science teams have been largely operating as researchers. Now, they’re being asked to operationalize their efforts and deliver quantifiable results to the bottom line,” said Patrick Dougherty, Rasgo founder and CTO. “This is a significant transition for data science teams. More often than not, unexpected process and technology limitations are unearthed, preventing teams from successfully making this transition. Rasgo’s feature store has already changed that paradigm for our customers, but there are so many more opportunities for us to amplify end user value. We’re thrilled to have the capital to hire and grow our world-class engineering team and develop new capabilities to contribute to the data science community.”

“Rasgo stands out as a best-in-class experience for feature engineering, helping data scientists and ML practitioners accelerate a traditionally manual process and transform raw data into actionable insights,” said George Mathew, Managing Director at Insight Partners. “The traction they have seen since founding exemplifies the need for a product that can help data teams increase efficiency for the whole organization. MLOps is a burgeoning sector that we are very excited about and are now thrilled to add Rasgo to our growing portfolio.”

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