Managed voice agent platform vs. streaming speech-to-text plus your own stack: how to choose

Managed voice-agent platforms such as Vapi, Retell, and OpenAI Realtime offer the fastest route to deploying standard phone or web conversational agents by bundling speech recognition, language models, speech synthesis, turn detection, interruption handling, and tool calling into a single service, while a self-composed stack using providers such as AssemblyAI, LiveKit, or Pipecat provides greater control over models, voices, conversation policies, costs, latency, and observability. The choice depends largely on whether a team needs a working agent quickly or requires custom logic, specialized models, licensed voices, detailed debugging, regulatory arrangements, or support for non-conversational functions such as captioning and voice search. The guide positions AssemblyAI’s Universal-3.6 Pro Realtime as a streaming speech-to-text layer compatible with either approach and highlights features including contextual transcription, speaker isolation, multilingual recognition, domain keyterms, configurable semantic turn detection, and low-latency streaming. It also explains implementation considerations such as managing WebSocket sessions, handling partial and final transcripts, passing agent responses back as context, integrating LLM and text-to-speech providers, and closing sessions to control billing. Pricing is presented as $0.45 per hour for the base real-time transcription service, with optional diarization, voice-focus, and medical-mode add-ons, while managed platforms generally simplify procurement but may limit optimization and transparency across the underlying pipeline.

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