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AI Voice Agent Development
The difference between a voice AI that feels natural and one that feels broken is latency. Above 700ms, callers start filling the silence. Above a second, they repeat themselves or hang up. We build voice agents that respond in under 500ms, which means tuning every stage of the ASR-LLM-TTS pipeline, not just picking an off-the-shelf provider.
We handle the full build: phone number provisioning, ASR integration, LLM response generation, TTS pipeline, interruption handling, escalation paths, and call analytics. You get a voice agent your operations team can monitor and your callers won't notice is automated.
Tell us about your call volume.
Eight components. Each one is necessary, a voice agent missing any of them will have obvious gaps in production.
We integrate and tune automatic speech recognition for your use case. Different domains (technical support, medical scheduling, retail) have different vocabulary that affects accuracy.
Optimised prompt design and model selection for real-time voice. Lower-latency models are used for quick turns; more capable models are reserved for complex reasoning steps.
Text-to-speech voice selection and audio streaming. We tune SSML markup, prosody, and pause timing so responses sound natural rather than robotic.
Callers interrupt. We build barge-in detection that stops playback immediately and processes the new utterance, critical for natural conversation flow.
The agent maintains conversation history and entity state across the full call duration. If a caller says their name in turn one, the agent uses it in turn ten.
When confidence is low, the request is out of scope, or the caller asks for a human, we hand off gracefully, including a real-time summary of the conversation for the human agent.
Every call is recorded, transcribed, and tagged. You get dashboards showing resolution rate, escalation rate, average handle time, and common failure topics.
We handle PSTN number setup via Twilio or a carrier of your choice. The agent accepts inbound calls and can make outbound calls from day one of launch.
There are three latency sources in a voice AI pipeline. Our <500ms target means each one gets a budget, and we optimise every stage to hit it.
We use streaming ASR that begins transcribing before the speaker finishes, reducing time-to-transcript. Provider selection matters here. We benchmark before choosing.
We select models with fast first-token latency and use streaming output so TTS begins before the full response is generated. Prompt caching reduces cold-start cost.
Streaming TTS pipelines begin audio playback on the first sentence fragment. We pick providers that offer real-time streaming rather than wait-for-full-text synthesis.
A fast agent that talks over the caller, mishears the account number, or cheerfully invents a policy is still a bad agent. Four things beyond raw latency decide whether a voice agent is one callers tolerate or one they hang up on.
Turn-taking. Humans signal when they are done speaking with tone and pauses, and they expect to be able to interrupt. We tune endpointing so the agent does not jump in while the caller is mid-sentence, and we build barge-in so the agent stops talking the instant the caller does. Get this wrong and every call feels like a fight for the floor, no matter how fast the responses are.
Real-world audio. Demo audio is one clear speaker in a quiet room. Production audio has accents, background noise, speakerphones, and cross-talk. We tune speech recognition for your callers and your vocabulary, and we build confirmation steps for the values that matter, so a misheard account number gets read back rather than acted on.
Knowing its limits.The fastest way to lose a caller's trust is a confident wrong answer. We give the agent a defined scope, a refusal path for anything outside it, and an escalation route to a human that carries a summary of the call so the caller never has to start over. The agent is built to hand off rather than to guess.
Doing real work. Answering questions is the easy half. The value is in the actions: booking the appointment in your calendar, updating the ticket, pulling the order status from your system of record. We build the tool integrations behind the voice so the agent actually resolves calls instead of just sounding like it might.
Four categories that account for the majority of voice AI deployments we've scoped and built.
Handles common support queries (order status, account questions, troubleshooting) end-to-end without a human, escalating only when the issue is outside scope.
Calls leads or existing customers to schedule, confirm, or reschedule appointments. Integrates with your calendar and CRM.
Handles initial inbound calls from prospects, asks qualification questions, and routes hot leads to your sales team with a full transcript.
Handles all calls when your team is unavailable. Resolves what it can, takes messages for the rest, and sends a summary to your team at the start of the next business day.
Projects where sub-second response time isn't required
If your use case is async (voicemail transcription, call summarisation after the fact), you don't need a real-time voice agent. The engineering cost and infrastructure complexity are only justified when the agent needs to hold a live conversation.
Very low call volumes (under 100 calls per month)
At under 100 calls per month, a human agent is almost certainly cheaper than building and maintaining a custom voice agent. Voice agents make economic sense at higher volumes where the automation ROI is clear. We will tell you this on the discovery call if it applies to your situation.
Highly regulated industries requiring 100% human oversight
If your regulatory environment requires a licensed human on every call, certain financial advice, specific medical contexts, a voice agent cannot handle calls autonomously. We can still build assisted-agent tooling that supports your human agents, but a fully autonomous voice bot may not be compliant.
Tell us your call volume, the use case, and the systems you need to integrate with. We'll reply within one business day with a rough scope and price range.