Voice-Native vs Chat-Derived
Voice-native platforms get designed for voice from the ground up — sub-500ms first-token latency, end-of-utterance detection that handles “umm” without hanging up, barge-in support, prosody control, and error-recovery flows when the speech-to-text mishears. The bolt-TTS-on-a-chat-agent pattern works for prototypes and demos and falls apart in production: a 2.5 second response gap that reads fine in chat sounds catastrophic on a phone call. The 2024-2025 wave of voice AI saw most chat-first vendors retrofit voice and most of those retrofits underperform a properly voice-native build by clear margins on hold time, AHT, and CSAT.
Sierra’s Position
Sierra, founded by Bret Taylor (former Salesforce co-CEO) and Clay Bavor, runs AI voice and chat agents for enterprise customer service. Their pitch is complex conversations rather than FAQ deflection: returns, billing disputes, subscription changes, troubleshooting flows that require multiple turns and decisions. Sierra has named customers including SiriusXM, ADT, OluKai, Sonos, and WeightWatchers. Pricing is per-resolution rather than per-seat, which aligns vendor incentive with deflection but requires careful definition of what counts as “resolved” — Sierra and the customer agree on resolution criteria per use case. Integrations cover Salesforce, Zendesk, Snowflake, and the major telephony platforms (Genesys, NICE, AWS Connect).
Other Players
The voice-native space in 2026 includes Rasa Pro for self-hosted, Google Dialogflow CX for Google-cloud shops with Vertex AI integration, Azure Communication Services and Copilot Studio for Microsoft stacks, AWS Connect with Lex and Bedrock for AWS shops, PolyAI for accent-heavy markets, Vapi and Retell AI for developer-first builds, and Cresta for the contact-center AI assistant pattern. Each has different strengths: Sierra and Decagon for managed service depth, Vapi and Retell for cost and flexibility, the hyperscalers for those with existing commits to consume. Evaluate on call volume, language coverage (Sierra supports 50+; many competitors are English-only), integration depth with your CRM, and cost profile per resolved call.
Deployment Considerations
Voice AI integration carries more complexity than chat. Telephony — SIP trunk, IVR replacement or sit-alongside, recording, transfer to human; CRM — screen pop, context handoff, post-call wrap; workforce management — Verint, NICE, Calabrio interactions for forecasting and scheduling; compliance — two-party consent recording laws (California, Florida, Pennsylvania, Massachusetts among the strict states), TCPA on outbound, and the EU AI Act Article 50 disclosure obligation that the caller is interacting with an AI. Budget six months for a voice deployment, not six weeks; budget integration cost at parity with platform cost.
Voice deployment cost model
Platform fee (per resolution) $0.85 - $4.50
Telephony (per minute) $0.012 - $0.025
LLM tokens (input + output) $0.04 - $0.18 per call
Recording storage + compliance $0.002 per minute
CRM integration (one-time) $80K - $400K
Workforce management integration $30K - $150KCommon Failure Modes
The recurring failures: deploying voice AI without redesigning the IVR around it (the agent inherits a 90-second menu before it ever speaks), forgetting to disclose AI nature on the call (EU AI Act Article 50 risk and a CSAT killer), under-investing in the human handoff so the customer repeats their problem from the start, and not running the full scenario library against the agent before launch.
Implementation Sequence
A defensible sequence: weeks 1-4, scenario inventory and integration design; weeks 5-10, build and instrument; weeks 11-14, internal call testing with a 100-call eval set; weeks 15-18, soft launch on a single skill at a single site; weeks 19-26, expand and tune. Run human-in-loop call review for the full first quarter.
What to do this week
Pull a week of recorded calls from your highest-volume queue and segment them: pure FAQ, multi-step routine, complex judgment. The mix tells you whether voice AI is a deflection play or a copilot play, and that decision changes the vendor shortlist.
