Build vs. buy: what you're really deciding with voice agents

A healthcare scheduling software company’s attempt to build an in-house voice agent illustrates how a quick demo can expand into months of unplanned work on real-time audio, telephony, model failover, state management, observability, interruption handling, and reliability at scale. The passage argues that voice AI is fundamentally more complex than adding audio to a chat workflow because conversational latency, endpoint detection, carrier behavior, and concurrent-call performance require specialized, ongoing engineering. It suggests that platforms can reduce delivery time by providing infrastructure, integrations, provider flexibility, and operational expertise, allowing product teams to focus on conversation design and core business workflows. Building internally may still be appropriate when a company has unique pipeline requirements, substantial existing voice infrastructure, strict data-processing constraints, or voice technology as a central competitive advantage, but for most SaaS companies treating voice as a product feature, the recommended approach is to use a platform, validate customer demand quickly, and avoid diverting engineering resources from the primary product.

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