A locally run voice stack can avoid a metered speech or language-model API when its models meet the required quality and latency. Compute, monitoring, staffing, carrier minutes, phone numbers, and any contracted support still cost money; capacity and utilization determine cost per call.
Data control depends on the whole path. Self-hosting can keep inference and stored transcripts within an agreed environment, while the phone carrier still transports the public-network leg. Map access, retention, consent, and subprocessors before making privacy claims for a regulated use case.
Self-hosting requires a server or VM, speech recognition, language and voice models, updates, monitoring, and recovery. A managed self-hosted arrangement can shift operations to a specialist, but its data boundaries and responsibilities must be explicit in the contract.
The cost crossover depends on model choice, hardware, utilization, reliability requirements, and the labor needed to operate the stack. Low-volume workloads often favor managed cloud APIs, while predictable high utilization can favor fixed-capacity infrastructure. A workload-specific total-cost analysis should decide the economics; data control and exposure to per-minute vendor pricing are separate decision factors.