For the past year, enterprise decision-makers have faced a rigid architectural trade-off in voice AI: adopt a “Native” speech-to-speech (S2S) model for speed and emotional fidelity, or stick with a “Modular” stack for control and auditability. That binary choice has evolved into distinct market segmentation, driven by two simultaneous forces reshaping the landscape.What was once a performance decision has become a governance and compliance decision, as voice agents move from pilots into regulated, customer-facing workflows.On one side, Google has commoditized the “raw intelligence” layer. With the release of Gemini 2.5 Flash and now Gemini 3.0 Flash, Google has positioned itself as the high-volume utility provider with pricing that makes voice automation economically viable for workflows previously too cheap to justify. OpenAI responded in August with a 20% price cut on its Realtime API, narrowing the gap with Gemini to roughly 2x — still meaningful, but no longer insurmountable.On the other side, a new “Unified” modular architecture is emerging. By physically co-locating the disparate components of a voice stack-transcription, reasoning and synthesis-providers like Together AI are addressing the latency issues that previously hampered modular designs. This architectural counter-attack delivers native-like speed while retaining the audit trails and intervention points that regulated industries require.Together, these forces are collapsing the historical trade-off between speed and control in enterprise voice systems.For enterprise executives, the question is no longer just about model performance. It’s a strategic choice between a cost-efficient, generalized utility model and a domain-specific, vertically integrated stack that supports compliance requirements — including whether voice agents can be deployed at scale without introducing audit gaps, regulatory risk, or downstream liability.Understanding the three architectural pathsThese architectural differences are not academic; they directly shape latency, auditability, and the ability to intervene in live voice interactions.The enterprise voice AI market has consolidated around three distinct architectures, each optimized for different trade-offs between speed, control, and cost. S2S models — including Google’s Gemini Live and OpenAI’s Realtime API — pro …
