Fenix Commerce Acquires Machine Learning Company Ocurate to Enhance E-commerce Capabilities

Fenix Commerce, a technology platform specializing in real-time delivery dates for e-commerce, has acquired Silicon Valley-based machine learning company Ocurate. This merger enhances Fenix's artificial intelligence and data capabilities, building on the incremental value it currently provides to customers. The integration of Ocurate's privacy-first individual-level event stream data and real-time machine learning expertise with Fenix's logistics, shipping, and inventory data processing enables new functionalities aimed at boosting conversion rates and average order values while reducing shipping costs and maximizing return on investment.

Akhilesh Srivastava, CEO of Fenix Commerce, emphasized the strategic alignment, noting that machine learning and real-time event stream data are crucial for maximizing ROI through customer interventions. The combined entity aims to unlock additional incremental revenue for e-commerce clients by enhancing existing features and introducing new capabilities. Fenix Commerce, already a market leader in estimated delivery dates, smart order routing, carrier rate shopping, and return logistics, will further strengthen its product offerings to improve not only conversion rates but also transaction values.

Tobi Konitzer, CEO of Ocurate, highlighted the opportunity to leverage data and machine learning to increase the ROI Fenix delivers. By integrating revenue, inventory, shipping, carrier events, and event stream data with foundational machine learning, the partnership provides a unique ability to maximize ROI and improve profit margins for retailers and shippers. This acquisition supports Fenix's mission to enhance commerce by improving the consumer online shopping experience from discovery to delivery and returns, ultimately increasing conversion rates, revenue, and profitability while reducing shipping spend and customer support costs. For more information, visit https://www.fenixcommerce.com.