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Announcing improvements to the Copilot similar tickets feature

Zendesk

Zendesk has enhanced its Copilot similar tickets feature with a hybrid retrieval model combining keyword and semantic matching, enabling agents to surface relevant historical solutions across all languages and channels without relying on generative AI or pre-configured intelligent triage topics. The update prioritises tickets resolved within the past 90 days and considers ticket subjects, descriptions, and initial comments to identify solutions even when customers describe issues using different terminology. Semantic matching capabilities will roll out over several hours to a week, whilst keyword matching is immediately available. For administrators, this represents a meaningful shift in how knowledge discovery works within Zendesk's ecosystem—the decoupling from generative AI and triage dependencies suggests Zendesk is prioritising retrieval accuracy and explainability over raw AI sophistication, which carries implications for teams already invested in complex entity classification or topic hierarchies that may now feel redundant.

Simultaneously, Zendesk introduced guided onboarding for Copilot auto assist, streamlining configuration into three steps: selecting knowledge sources, defining user access, and publishing AI-generated procedures. This reduction in setup friction addresses a persistent friction point in AI adoption within support operations, though the requirement to manually tag tickets with agent_copilot_enabled remains a potential bottleneck for teams managing high-volume queues. The timing of both announcements signals Zendesk's strategic focus on lowering barriers to Copilot adoption whilst improving the quality of agent-facing suggestions—a necessary counter-move as competitors like Salesforce expand agentic capabilities across their CX platforms. For CX leaders evaluating whether to deepen Copilot investment, the question becomes whether these incremental improvements in retrieval and onboarding are sufficient to justify the feature's cost and complexity, or whether the real competitive pressure now lies in autonomous agent capabilities rather than agent-assist tools.