PulseCX: Breaking the Closed-World Assumption in Real-Time CX
For conversational AI agents in dynamic customer experience environments, PulseCX addresses the bottleneck of real-time knowledge integration.
PulseCX tackles the closed-world assumption in real-time customer experience by decoupling knowledge acquisition from consumption, achieving <10ms overhead and significant gains in Intent Resolution and Customer Satisfaction.
Conversational AI agents in Customer Experience (CX) typically suffer from a Closed-World Constraint, ignoring high-velocity external shifts like viral trends or outages. Ad-hoc web search attempts to bridge this gap but often introduce prohibitive latency and context poisoning. We introduce PulseCX, a framework that decouples knowledge acquisition from consumption. Adopting a structure-first paradigm, PulseCX employs an asynchronous agent to linearize signals into a Decay-Aware Temporal Knowledge Graph (DA-TKG) governed by reinforcement--decay dynamics to actively manage information lifecycles. By coupling this self-evolving memory with hierarchical intent gating, PulseCX removes synchronous search bottlenecks (<10ms overhead) and drives significant gains in Intent Resolution (IRR) and Customer Satisfaction (s-CSAT) in dynamic environments.