Cloud AI receptionist platforms typically charge per minute of conversation, which means your operating cost scales linearly with usage. Self-hosted AI runs on fixed infrastructure — the cost per call falls as call volume rises, and there is no per-minute metered vendor markup.
Data sovereignty is the other key dimension. A cloud AI receptionist sends call audio, transcripts, and caller information to a third-party vendor's infrastructure. A self-hosted deployment processes that data on hardware the business controls — meaning caller PII, medical intake details, and legal context stay within the operator's environment.
Self-hosting requires infrastructure to manage: a server or VM, the voice stack (STT, LLM, TTS), and update and monitoring routines. For a business without technical staff, a managed self-hosted deployment — where an agency owns and operates the stack on your behalf — captures most of the data-control benefit without the operational burden.
At a practical crossover point of roughly 100,000 to 300,000 monthly AI requests, self-hosting typically becomes cheaper than cloud API pricing. Below that volume, cloud API pricing may win on raw compute cost, but the data-control and per-minute-pricing arguments still favor self-hosting for regulated industries.