AI · 2026年10月4日
Quiq launches Voice Assist agentic AI for live call support
Quiq has launched Voice Assist, an agentic AI tool that listens to live calls, surfaces real-time guidance, and can act on an agent's behalf without screen-switching.
What happened
Customer service AI vendor Quiq has launched Voice Assist, an agentic AI tool designed to support human agents during live phone calls. The system listens to conversations in real time, surfaces contextual prompts and guidance, and can also take actions on the agent's behalf — such as pulling up account information or initiating back-end processes — without the agent needing to switch screens or manually search for answers.
Unlike conventional call-centre AI tools that summarise calls after the fact or offer static scripts, Voice Assist is positioned as an in-the-moment assistant that works alongside the agent throughout the interaction, combining real-time guidance with the ability to execute tasks autonomously.
Why it matters
Voice Assist reflects a broader shift in contact-centre technology from AI that analyses conversations afterwards to AI that actively participates in them as they happen. By giving agents live, context-aware prompts and handling routine actions in parallel, the tool is designed to reduce the cognitive load on agents during calls — potentially shortening handle times and reducing errors that stem from manual lookups or distracted multitasking.
For organisations investing in agentic AI, this launch is a signal that the technology is moving beyond chat and back-office automation into the highest-pressure, highest-stakes channel: the live voice call. How well agents trust and adopt such tools — rather than treating them as a distraction — will likely determine whether the promised efficiency gains materialise.
The Renascence take
The real test of a tool like Voice Assist won't be its technical capability but whether agents actually let it act on their behalf mid-conversation, under pressure, with a customer listening.
Agentic AI during live calls is as much a trust-design problem as it is an engineering one. If an agent has to stop and verify what the AI just did before continuing the conversation, the "efficiency" gain disappears and cognitive load actually increases. The operators who get value from tools like this will be the ones who redesign agent workflows and training around the AI's actions — not those who simply bolt it onto existing scripts and call it transformation.
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