Reltio has unveiled its latest product release featuring new capabilities designed to enhance customer experience and bolster security through advanced AI-powered features.
The announced upgrades include the ability to segment customers based on interactions and behaviour, integration with partners, and the introduction of native multi-factor authentication (MFA). Also highlighted is the general availability of Reltio's AI-powered Flexible Entity Resolution Networks (FERN).
Reltio aims to strengthen its data unification offerings, specifically for multidomain Master Data Management (MDM) and customer 360 profiles, by integrating dynamic segmentation and pre-trained large language models (LLMs) into its platforms. These models are built for out-of-the-box individual and organisation data matching.
With the increasing demand for improved customer experiences, organisations require reliable, unified data. Reltio's data unification capabilities offer firms a richer understanding of customer behaviours, enabling them to create more personalised experiences. This can lead to improved customer engagement, the effectiveness of marketing programs, and enhanced customer acquisition and retention, all while maintaining data security.
A significant feature of this release is enhanced dynamic segmentation. The Reltio Customer 360 platform can now create customer segments that are based not only on purchases but also on a variety of interactions such as claims or call centre activity. This approach allows businesses to develop high-quality, actionable customer segments aimed at better customer experiences, retention, and growth.
Security enhancements in this release include the introduction of native MFA in addition to existing features like Single Sign On (SSO) and client-credential verification, improving overall enterprise security for core data systems. The Reltio Trust Center has also been introduced to assist with compliance reporting.
FERN offers an AI-powered solution for customer-data matching, reducing the person-hours typically required with traditional machine learning approaches. The entity resolution mechanism employed by FERN requires no additional training, and the system is designed to operate securely and privately, with customer data remaining within the Reltio-managed tenant. This matching engine uses LLMs trained on extensive text data, allowing for semantic understanding and uncovering matches that older, rules-based systems would miss.
The update includes expanded integration with data-governance products to streamline the discovery of trusted data assets and enable the development of data products for enterprises. Incorporating Microsoft Purview Data Governance and recent integrations with Collibra's data catalog enhances the management of metadata for customers, providing efficiencies and cost savings by negating the need for costly custom-built integrations.
The release reflects an effort to alleviate the extensive data stewardship and IT workload involved in creating unique, trusted records. According to Venki Subramanian, Senior Vice President of Product Management at Reltio, "It takes extensive data stewardship and IT effort to build unique, trusted records. Data teams create, weight, and fine-tune match rules across millions of records and thousands of matching edge cases, for data points like nicknames, abbreviated addresses, and more."
He further noted, "We've tapped into the power of AI, specifically Large Language Models (LLMs), to streamline and simplify that process along with improving accuracy to further ensure data leaders are fully empowered to provide high-quality data at the speed of business through our AI-driven platform."
