Voice agents built
on Vapi.
Vapi wires speech-to-text, an LLM, and text-to-speech into one real-time call pipeline, so we spend our time tuning the conversation — intent detection, interruption handling, when to escalate — instead of hand-building the plumbing between three separate providers.
Serving UK and EU clients: GDPR, EU AI Act, and data residency are covered on our Trust & Safety page.
One pipeline,
three providers.
Vapi is a voice AI orchestration platform: it handles the real-time audio streaming, turn-taking, and interruption logic that sits between a transcription provider, a language model, and a text-to-speech provider — the parts that are genuinely hard to get low-latency and reliable from scratch.
What we bring is everything around that: which providers to use, how the agent should actually behave on a call, and where it should hand off to a human. See our live voice demo — it's the real pipeline, not a scripted mockup.
The same combination
running in our demo.
Swapped per project when a client's language, latency, cost, or voice requirements point elsewhere — but this is where we start.
Low-latency transcription tuned for real-time conversation, not batch transcription.
Reasoning and tool use for the conversation itself. See our Claude development page.
Natural-sounding voice output, tuned for the persona a given deployment needs.
Part of our
voice AI work.
Vapi is the orchestration layer underneath the voice agent work we do end to end.
Telephony integration, intent detection, and out-of-scope handoff — the full service this sits inside.
Hear the actual Deepgram / Claude / ElevenLabs pipeline running, not a description of it.
What happens when a voice agent gets asked something outside its scope, and how we design for it.
Before you
book a call.
The questions we get asked most about Vapi and our voice stack — answered straight, no sales pitch.
What is Vapi and why use it for voice agents?
Vapi is a voice AI orchestration platform that wires together speech-to-text, an LLM, and text-to-speech into one low-latency call pipeline, so we're not hand-building the real-time plumbing between three separate providers for every project. We still choose and tune which providers sit behind it for each client.
Which providers do you use behind Vapi?
Our default stack pairs Deepgram for speech-to-text, Claude for the model, and ElevenLabs for the voice — the same combination running in our live demo. We'll swap any of these if a client's requirements (language, latency, cost, voice) point elsewhere.
Can we hear this before committing to a project?
Yes — try our live voice demo. It's the same pipeline described on this page, not a scripted mockup.
Tell us what
you're trying to build.
Book a 30-minute call — or try the live demo first and see what a real deployment sounds like.