RingCentral has unveiled new enhancements in customer experience technology with the introduction of its new Customer Journey Analytics and the general availability of AI Agent Assist. These innovations, part of the RingCX platform, offer organisations a unified, AI-driven approach to understanding and optimising the complete customer journey across both UCaaS (Unified Communications as a Service) and CCaaS (Contact Centre as a Service) environments.
“The contact centre industry has been solving problems in isolation for too long,” said Jim Dvorkin, SVP of Customer Experience Products at RingCentral. “What we’re delivering is complete customer intelligence—comprehensive analytics that capture every voice conversation detail. When you can see the full customer journey AND have AI actively improving every interaction in real-time, that’s when breakthrough customer experiences happen.”
Bridging the Experience Gap Across Communication Channels
One of the biggest pain points in today’s customer experience landscape is the fragmentation caused by siloed systems. Customer interactions often span multiple channels and platforms, creating disjointed experiences and data gaps. RingCentral addresses this challenge by offering Customer Journey Analytics that provide end-to-end visibility across all communication touchpoints—whether the interaction starts in RingCX or transitions to a RingEX expert.
By integrating analytics within a unified communication framework, RingCentral enables businesses to understand not only what is happening in every interaction, but also why. Organisations gain deep visibility into every step of the journey, allowing them to deploy intelligent routing strategies, boost team collaboration, and equip agents with the right information exactly when they need it.
Turning Insight into Real-Time Action with AI
Building upon this robust data foundation, RingCentral’s suite of AI tools transforms customer insights into powerful, real-time action. Now generally available, AI Agent Assist acts as a smart assistant for customer service representatives. Drawing from the organisation’s entire knowledge base and powered by full interaction history, this feature delivers timely, context-aware responses that significantly reduce resolution times and improve first-call accuracy.
In addition, AI Interaction Analytics—now in beta—leverages advanced sentiment analysis and predictive modelling to process 100% of customer interactions. This gives organisations a proactive way to identify issues before they escalate and predict customer satisfaction (CSAT) scores with precision. When integrated into the larger analytics framework, these AI tools don’t just monitor performance—they actively shape it.
Another key innovation introduced is Agent Screen Recording, currently in beta, which gives supervisors a detailed view of agent workflows. When combined with journey analytics and AI-driven insights, this functionality allows for precision coaching and performance management grounded in real-time, context-rich data.