An AI voice agent stacks telephony, streaming speech-to-text, a language model with tool access, and text-to-speech, all wired to your live systems.
A production AI voice agent is a pipeline of four layers plus your integrations. Telephony carries the call over SIP or a provider like Twilio. Streaming speech-to-text transcribes the caller in real time, and for Indian languages we use Sarvam AI because English-first engines fail on Indian audio. A language model with tool access is the brain: it understands intent, decides what to do, and calls your systems to actually resolve the request. Text-to-speech streams a natural voice reply back. Around that sits the orchestration layer that manages turn-taking, interruptions, and escalation, plus the API integrations into your CRM, scheduler, or billing that let the agent act rather than just talk. The exact components vary; the architecture is consistent.
The integrations are the hard, valuable part. Anyone can wire four managed services into a demo; making the agent reliably read and write your live systems under real call conditions is the engineering.
Streaming across every layer is what makes it feel human. Batch each stage and you get robotic pauses; overlap transcription, reasoning, and synthesis and the caller hears a natural reply.
Book a 30-minute call and get a straight answer from the engineer who builds these systems, not a sales rep.