DataStax takes over Machine Learning company Kaskada
The real-time AI company, DataStax announced that it has entered into a definitive agreement to acquire Kaskada, a machine learning (ML) company.
Both DataStax and Kaskada have a track record of contributing to open source communities. Datastax will open source the core Kaskada technology initially, and it plans to offer a new machine learning cloud service later this year.
Most machine learning initiatives don’t deliver the results that businesses need because the process is manual, complex and frustrating Compounding this problem, many models underperform because they lack the relevance and context of real-time data. The addition of Kaskada to DataStax’s portfolio of cloud services—which today includes the massively scalable Astra DB database-as-a-service built on Apache Cassandra and event streaming with Astra Streaming— will give organizations a single environment to easily and cost-effectively deliver applications infused with real-time AI, using an advanced ML/AI model proven by industry leaders such as Netflix and Uber.
“Businesses must operate in real time, using data to power operations and fuel instant, informed decisions and actions,” said Chet Kapoor, DataStax chairman and CEO. “DataStax has a disproportionately high number of customers using real-time data, and with Kaskada as part of our services portfolio, we can give them the opportunity to use that data to create powerful experiences for their customers with real-time AI. It’s an exciting time for DataStax, and we have a clear new mandate: make it possible for anyone with real-time data to do real-time AI.”
“Many companies struggle to see success with their big data projects because they don’t have the luxury of large ML and data engineering organizations–the cost is large and the time to impact is long,” said Davor Bonaci, Kaskada CEO. “We’re thrilled to join forces with DataStax to enable the real-time AI stack that just works, fueled with data from Astra DB.”
AI at Scale: Game-changing potential, but hard to achieve
According to Gartner, “By 2027, over 90% of new software applications that are developed in the business will contain ML models or services as enterprises utilize the massive amounts of data available to the business. These models will add data-driven intelligence to applications by integrating models that deliver next best actions, forecasts, scoring, risk assessment and many other attributes for both customer and employee transactions.”
“The emergence of intelligent applications infused with personalization and artificial intelligence impacts requirements for operational data platforms to support real-time analytic functionality. The need for real-time interactivity means that these applications cannot be served by traditional processes that rely on the batch extraction, transformation and loading of data from operational data platforms into analytic data platforms for analysis. Instead, they rely on analysis of data in the operational data platform to accelerate decision-making or improve customer experience.
The Kaskada technology is designed to process massive amounts of event data as streams or stored in databases and its unique time-based capabilities create and update features for ML models based on sequences of events, or over time. It enables customers to adapt to rapidly evolving content and asynchronously creates features, allowing applications to use millions of predictions based on unique contexts.
DataStax has launched a new look and feel for the company as part of their evolution to becoming the real-time AI company delivering a high-scale database, advanced event streaming and now real-time AI that helps customers build fast and scale without limits. The company logo and overall corporate identity have been refreshed with new colorways and treatments which have just rolled out.
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