Agentic AI in the contact center: autonomous agents and the STT layer
Blog post from Gladia
Agentic AI contact centers rely on speech-to-text (STT) as the foundational layer that converts live customer audio into the text used by LLMs, CRM systems, quality assurance tools, routing workflows, and compliance records. The article argues that transcription mistakes, particularly involving account numbers, names, intent phrases, disclosures, or speaker attribution, can silently trigger incorrect automated actions even when overall word error rates appear acceptable. It contrasts autonomous agents, which use natural-language reasoning and external tool calls, with traditional decision-tree IVR systems, and recommends a phased rollout from post-call transcription and automated QA to real-time agent assistance, autonomous routing, and multilingual scaling. Key evaluation factors include accuracy on real production audio, entity-level reliability, language and accent coverage, low streaming latency, auditability, data governance, and total feature costs. The vendor positions Solaria-3 for asynchronous European business-audio transcription and Solaria-1 for low-latency, multilingual real-time streaming, while noting that speaker diarization is available only after calls are completed.
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