Data warehouse provider Snowflake announced the acquisition of Myst AI. Snowflake is expected to leverage the startup’s time-series forecasting technology to further optimize its data cloud with ML functionality.
Financial details weren’t disclosed. Myst AI primarily develops AI applications for the energy sector. Its platform helps develop AI models for business predictions. The energy sector uses these models to predict fluctuations in power prices, consumer energy demand and other trends.
The startup’s platform focuses on developing neural networks that process so-called time-series data. The platform provides users with pre-built neural networks as well as connectors for collecting time-series data such as weather data. Users can process data to train pre-built neural networks that perform specific tasks. Think of predicting changes in energy demand.
Furthermore, the technology helps developers test the accuracy of AI models before they go into production. For starters, newly developed neural networks can determine how an old business event ended. This determination can then be tested against historical data about this event to determine the accuracy of the AI model in question.
ML applications for Data Cloud
Snowflake says it’s eager to use the startup’s technology for time-series prediction capabilities. The organization is committed to investing more in machine learning capabilities for its data cloud platform in the coming years.
Time-series forecasting is used for supply chain management, inventory planning and financial applications. According to Snowflake, the technology is particularly interesting in the healthcare, manufacturing and energy sectors.
Last year, Snowflake acquired Streamlit. The AI firm provides a software tool that allows developers to build interfaces for AI and other data science applications.