DataStax Purchases Kaskada, A Machine Learning Business

DataStax, a real-time AI startup, announced that it has signed a binding agreement to acquire Kaskada, a machine learning (ML) startup that pioneered the problem of managing, storing, and accessing time-based data for behavioural ML model training and delivering the quick, useful insights that underpin AI (AI).
DataStax and Kaskada both have a history of giving back to open source communities. Datastax intends to launch a new machine learning cloud service later this year and will first open source the key Kaskada technology.
Due to the laborious, complicated, and irritating nature of the process, the majority of machine learning programmes don’t produce the outcomes that organisations need. This issue is made worse by the fact that many models perform poorly due to a lack of real-time data’s context and relevance. With the addition of Kaskada to DataStax’s suite of cloud services—which already includes the massively scalable Astra DB database-as-a-service built on Apache Cassandra® and event streaming with Astra Streaming—organizations will have access to a single environment where they can quickly and affordably deliver applications with real-time AI using an advanced ML/AI model that has been successfully implemented by market leaders like Netflix and Uber.
According to Chet Kapoor, chairman and CEO of DataStax, “businesses must operate in real time, using data to power operations and fuel fast, informed decisions and actions.” “DataStax has a disproportionately large number of customers who use real-time data, and now that Kaskada is a part of our services portfolio, we can give them the chance to use that data to develop effective real-time AI experiences for their consumers. DataStax is in an exciting phase right now, and we have a clear new mission: “Make real-time AI accessible to anybody with real-time data.”
Because they lack the luxury of massive ML and data engineering organizations—whose costs are high and whose time to impact is lengthy—many companies struggle to see success with their big data projects, according to Davor Bonaci, CEO of Kaskada. We are overjoyed to work with DataStax to make real-time AI stack possible that is powered by data from Astra DB.
Aiming for game-changing AI at scale is challenging.
By 2027, over 90% of newly created commercial software applications will integrate machine learning (ML) models or services as businesses make use of the enormous volumes of data at their disposal, predicts Gartner. By including models that provide next best actions, forecasts, scoring, risk assessment, and many other aspects for both consumer and staff transactions, these models will provide data-driven intelligence to apps. ”
“The requirements for operational data platforms to provide real-time analytic functions are impacted by the rise of intelligent applications enhanced with personalisation and artificial intelligence. These applications cannot be supported by conventional processes that rely on batch data extraction, transformation, and loading from operational data platforms into analytic data platforms for analysis since they require real-time interactivity. Instead, they rely on the operational data platform’s data analysis to hasten decision-making or enhance the client experience.
The Kaskada technology is made to process enormous volumes of event data that are kept in databases or as streams, and thanks to its special time-based capabilities, it can build and update features for machine learning models based on time-based or event-based sequences. Customers can respond to quickly changing content because to its ability to asynchronously develop features and use millions of predictions depending on certain scenarios.
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To give customers the most memorable experiences in e-commerce, you need to be able to act instantly on insights, which calls for the use of machine learning on real-time transactions. Priceline’s CTO Martin Brodbeck. “Astra DB is a potent part of the Priceline data architecture, and millions of consumers use our website and mobile apps at any given time. In order to feed our bigger customer ecosystem, our machine learning algorithms employ vast data sets to produce insightful client information, improved personalisation, and better travel recommendations.
As part of their transformation to become the real-time AI company, DataStax has unveiled a new brand identity. They now offer a high-scale database, enhanced event streaming, and real-time AI that enables customers to build quickly and scale without boundaries. With new colours and treatments that have recently launched, the company logo and overall corporate design have been updated.