The audio never leaves the building.
Anuvo Resident is the self-hosted edition: a voice agent that runs entirely inside your infrastructure, answers in 355 ms — measured — and has no third-party model dependency at all.
Most on-premise voice stacks sit above a second of latency. Anuvo Resident delivers sub-400 ms answers inside your own network — no per-minute API fee, no vendor repricing risk, no audio leaving the building. This is the edition that unlocks regulated buyers: hospitals, labs, legal.
The businesses with the most calls and the most sensitive data were locked out
Cloud voice AI sends every word of every call to somebody else's servers and charges per minute, forever. For a hospital, a lab or a law firm that is a compliance problem dressed as a convenience — so the businesses that need a voice agent most were carrying a risk nobody had priced.
Anuvo Resident removes the trade. The entire stack — speech recognition, synthesis, orchestration, audit log — runs on hardware you control. What the cloud edition does for a commercial buyer, Resident does for a regulated one.
Data residency, by design
Audio, transcripts and metadata live and die on your network. Compliance stops being the reason you cannot use AI.
Sub-second, on-premise
355 ms measured inside the customer network — not a marketing number, a benchmark with a published method.
No vendor repricing risk
Your inference cost is your hardware cost. No model vendor can reprice your per-minute bill out from under you.
Multilingual, on your floor
English, Hindi and regional languages run locally. Intake, booking and FAQs in the caller's language, per line.
Integrates with what you run
PBX or SIP trunk in, HIS / EHR / CRM out via REST and webhooks. The agent books into your systems, not ours.
Audit logging you control
Every call recorded with consent, every action logged, RBAC enforced — and the log never leaves your network either.
One appliance or your existing Kubernetes — your call
Anuvo Resident deploys as a packaged stack: a single appliance for most sites, or a Helm chart into an existing cluster for teams that already run one. The architecture is identical either way.
What a deployment needs
| Site size | Hardware profile | Throughput | Notes |
|---|---|---|---|
| Clinic / small practice | 1 appliance (GPU-optional, CPU-capable) | ~4–6 concurrent calls | Single box, single number, multilingual lines. |
| Multi-branch hospital | 2–4 appliances or a small cluster | ~20–40 concurrent calls | Active/active, N+1 for the media layer. |
| Lab chain / enterprise | Existing Kubernetes + GPUs | Scaled horizontally | Helm chart, autoscaling, central audit store. |
Concurrency planning, region choice and a full component checklist drop out of the architecture planner — run your own numbers before you talk to sales.