Self-hosted voice AI runs the whole agent inside your network — in 355 ms.
Anuvo Resident is self-hosted voice AI: speech recognition, orchestration and synthesis all run on your hardware, with no third-party model dependency and no audio leaving the building. Measured end-to-end: 355 ms.
The old assumption — that on-premise voice stacks sit above a second of latency — is exactly the myth we built Resident to break. Residency and speed are not a trade-off.
When "the cloud" is the answer nobody can sign
Cloud voice AI made agents possible, but it sends every word of every call to somebody else's servers and charges per minute, forever. For hospitals, labs, law firms and public-sector buyers, that is a compliance problem dressed as a convenience.
No audio egress
Audio, transcripts and metadata resolve inside your network. "Where does the audio go?" — nowhere.
No vendor repricing risk
Your inference cost is your hardware cost. No model vendor can reprice your per-minute bill out from under you.
355 ms, on your floor
Sub-400 ms is not a cloud-only trick. The same latency budget runs in your building — see the benchmark method.
What "self-hosted" actually means here
A packaged stack, not a research project: one appliance for most sites, or a Helm chart into your existing cluster. Same agent behaviour as Cloud — different physics.
What a deployment needs
| Site size | Hardware | Concurrency |
|---|---|---|
| Clinic / small practice | 1 appliance, CPU-capable | 4–6 calls |
| Multi-branch hospital | 2–4 appliances or a small cluster | 20–40 calls |
| Lab chain / enterprise | Existing Kubernetes + GPUs | Scaled horizontally |
Sizing, region choice and a full component checklist drop out of the architecture planner. Run your own numbers before you talk to anyone.