AI That Responds While the Moment Still Matters

For voice conversations we usually target a p95 turn latency under one second, which feels natural to most callers. Streaming captions can appear in a few hundred milliseconds, and fraud scoring in the request path often needs well under 100 ms. We set the target with you and measure it from the prototype onward.

A working prototype starts from $2,500, a production feature from about $15,000 and a multi-region platform from $45,000. Running costs are mostly per audio minute or per event, and we estimate them before you commit.

Speech-to-speech APIs like OpenAI Realtime and Gemini Live give the lowest latency and the most natural turn-taking. A separate pipeline gives more control over each step, custom vocabulary and voice choice. We prototype both when the choice is not obvious.

Yes. We build consumers that enrich events, call models and publish results to new topics, with backpressure, retries and dead-letter queues. Your existing producers do not need to change.

We set timeouts per hop and fall back to a faster model, a cached answer or a simpler response path. Monitoring alerts us when p95 latency drifts, and traffic can shift to another region or provider.

Yes. We connect SIP trunks and providers like Twilio alongside WebRTC for browsers and mobile apps, so the same AI can serve calls, apps and web widgets.

Streaming speech models handle most accents well, and we add custom vocabulary for product names and technical terms. We measure word error rate on recordings from your own callers before launch.

Yes. Open-weight speech and language models can run on your GPUs with vLLM or Triton, which helps with data residency and cost at high volume. We size hardware from your peak concurrency.

You own the code, infrastructure definitions and configuration. We hand over runbooks and load test scripts so your team can operate and scale it.