Voice AI
Voice AI is the application of AI to spoken-language interfaces, voice agents, contact-center automation, and IVR replacement.
Voice AI is the application of AI to spoken-language interfaces. The category covers voice agents for customer service, contact-center automation, IVR (Interactive Voice Response) replacement, and any system where the primary interaction is voice rather than text.
A typical voice pipeline combines speech-to-text, language understanding or a language model, and text-to-speech, with latency budgets tight enough to feel conversational. In support, voice AI handles inbound calls, authenticates callers, answers routine questions, and hands off to a human with a summary when needed. The hard problems are accents and background noise, interruptions, and knowing when a caller should be transferred rather than kept in an automated loop.
In context
Voice AI converged with text AI in 2024-2025. The same LLMs and AI agents that power chat now power voice, with speech-to-text and text-to-speech layers wrapping the model. Latency is the dominant engineering constraint, sub-second response is required for natural conversation.
Voice-first vendors (Sierra, Retell AI, Ringg AI) specialize in ultra-low latency. Voice-as-channel vendors (Cresta, Cognigy, Decagon) treat voice as one of several channels with shared underlying intelligence.
The 2026 reality: voice AI in customer service handles tier-1 inquiries (status, scheduling, simple changes) reliably; complex multi-step conversations still benefit from human-in-the-loop fallbacks.
How Auralis uses Voice AI
Auralis supports voice as a channel alongside chat, email, and ticket queues. The underlying intelligence is shared; the channel-specific layers handle latency and I/O.