Voice AI Agent Development — Real-Time Agents That Take Interruptions, Phone Calls, and a Compliance Review.

It designs and builds software agents that hold spoken conversations in real time, on phone lines, in apps, and inside video calls. That covers the speech pipeline (speech recognition, an LLM, and speech synthesis, or a speech-to-speech model), barge-in and turn-taking, SIP or WebRTC transport, integrations with business systems, and compliant deployment. Trembit specialises in the real-time layer that decides whether an agent feels like a conversation.

Often, yes, at first. A managed platform is usually the fastest and cheapest way to validate a voice use case at modest volume. A custom build pays off when audio must stay in the EU or on your servers, when the agent must fit an existing PBX, when per-minute pricing dominates your costs, or when you need latency control the platform doesn’t expose. We build on these tools where they fit.

Industry-reported ranges put a human-feeling first response at roughly 500–1,200 ms, with later turns around 300–600 ms. Past about two seconds, callers assume the call dropped. Well-tuned cascaded pipelines can reach sub-second responses, while many production agents sit nearer 1.4–1.7 seconds. What you get depends on model choice, transport, geography, and endpointing, so we set a budget per stage and measure against it on real networks.

Barge-in needs full-duplex audio: the agent keeps listening while it speaks. When voice activity is detected, we cancel the response and flush audio already queued in playout buffers, otherwise the caller hears half a sentence after interrupting. We also tune jitter-buffer depth, because it delays detection itself. Turn-taking, deciding the caller has finished, is a separate problem, and we tune it separately.

Yes. Agents connect to SIP trunks and the public phone network, and can sit beside an existing FreeSWITCH or Asterisk PBX or contact-centre stack, including handoff to human agents with context. We keep AI inference off the switch’s media threads so slow model calls don’t stall other callers, and we tune recognition for narrowband phone audio, which behaves differently from a browser microphone.

Voice AI can be used under HIPAA when every vendor that touches patient audio signs a Business Associate Agreement covering that specific service and modality. Coverage for text doesn’t automatically extend to audio: when we last checked (July 2026), the OpenAI Realtime API’s audio modality wasn’t on Azure’s HIPAA-eligible list. We map the BAA chain per vendor and use self-hosted speech models where coverage is missing. Trembit signs a BAA when our team handles PHI.

Yes. We design voice pipelines for EU hosting or fully on-premises deployment, including self-hosted speech recognition and synthesis, so raw audio never reaches a third-party API. Our real-time speech-to-text system for a media company runs on the client’s own GPU infrastructure, with no audio sent to external services. Managed platforms offer EU regions too; check that every component, including telephony and logs, stays in-region.

There’s no single price; cost follows scope. The main drivers are call volume and peak concurrency, cascaded or speech-to-speech architecture, self-hosted or API-based models, telephony and PBX integration, number of languages, systems the agent must act in, and compliance and data-residency requirements. We give a firm estimate after a scoping call rather than a rate card. Running costs are broken down in our voice AI platform cost guide.

A voice AI proof of concept takes 4–8 weeks and runs on real calls with your domain vocabulary and flows. A production voice agent typically takes 3–5 months. The timeline depends on the number of call flows and languages, telephony and system integrations, and compliance review. The first milestone is an agreed latency budget and architecture, usually within the first two weeks.

Yes. We migrate legacy IVR to a conversational voice agent incrementally, starting with the highest-volume call types and keeping the existing IVR as a fallback during the transition. Callers who need a person are handed to a human agent with the conversation context, so they don’t repeat themselves. Rollout expands call type by call type as each one proves itself in production.

Yes. We choose speech models per language, detect the caller’s language early in the call and switch flows, and test on the accents and phone-line audio your callers actually have. Our voice recruiting agent screens candidates in more than one language, and our healthcare translation work runs real-time speech recognition across multiple clinical language pairs.

You do. The source code, prompts, conversation flows, and evaluation sets we build are yours, and recordings and transcripts stay in your accounts or infrastructure under your retention rules. We use third-party models through your own API accounts wherever possible, so you can change vendors or bring the work in-house without a rebuild.