SymphonyAI Announces New Capabilities for Its Eureka AI Platform

SymphonyAI, a leader in high-value enterprise AI SaaS for strategic industries, announced today new capabilities for its Eureka AI platform that bring real-time understanding and visualization to the technologies that underpin its vertical businesses, driving faster time-to-insights and deeper understanding for data scientists and business users.

New explainable segmentation capabilities in Eureka help users quickly find previously undiscovered relationships in data that are indicative of factors such as higher product quality or drivers of revenue. The segmentation capabilities are driven by an ensemble of unique, unsupervised learning algorithms that outperform traditional clustering algorithms, enabling real-time tracking and dynamic recommendations for use in multiple industries.

The Eureka platform is further bolstered by technology innovations from the verticals, particularly SymphonyAI Sensa, which developed the ability to visualize complex data transformations powered by GraphQL to enable data science and business teams to run seamless workflows, speeding time-to-insights for users to identify, understand, and deliver business value as the underlying conditions of their data changes.

"Being able to improve our manufacturing processes through tuning and insights has enormous implications on revenue, quality, customer satisfaction, and sustainability initiatives at Western Digital. Eureka's segmentation capabilities give us a new understanding of ways in which to improve our processes," said Gautam Khera, Western Digital senior global director, advanced product management and engineering. "With their technology, we identify segments of data, and distinctive factors driving them, that we couldn't have uncovered otherwise. For example, such findings helped us reduce our root mean square error by 19 percent in testing - a significant cost- and time-saver that would enable faster production."

Eureka enables data scientists and business experts alike to rapidly build, deploy, and scale AI and machine learning models and applications spanning SymphonyAI's verticals. The platform provides users with capabilities ranging from data harmonization across silos, data exploration, feature engineering, model building, model deployment, and scaling. Data scientists and business users also benefit from Eureka's library of pre-trained models to solve problems such as identifying relationships between attributes to create segments that were previously obscured.

For example, the retail sector relies on rapid customer segmentation in order to understand changing patterns of demand. Decisions such as how much product to carry in-store or online, what kinds of promotions to run, and what brands to order are all determined by recommendations from algorithmic segmenting, and they can be revised as often as daily. This kind of dynamic decision-making can only be supported by understanding the unique attributes driving changing customer demand and how those attributes are correlated, a key benefit as the platform evolves.

"We built Eureka because we saw the need for an AI platform that was optimized for specific business use cases across key sectors that couldn't be as effectively served by a general platform," said Vijay Raghavendra, CTO of SymphonyAI. "As the business has grown and technology needs have shifted, we've seen a consistent need across our verticals and the broader AI market for a truly end-to-end AI platform - one that could uncover 'unknown unknowns', group those by unique factors, and clearly show data scientists and business users alike why those factors were important and suggest an appropriate response. Critically, this platform eliminates the need to hand off data and findings from one team to another, a common friction point in most AI processes. We're using our own internal innovation to enhance Eureka to support this end-to-end vision for businesses users and data scientists operating across all the industries we serve."

"We built the Sensa platform to operationalize our machine learning models into reusable, highly available and scalable, cloud-native software components, to unlock the critical insights derived from model-based decision-making," said Sensa CTO Warren Zafrin. "We are thrilled that not only will Sensa customers benefit from these innovations, but so will other SymphonyAI customers in other industries."

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