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What is Sierra?
Enterprise conversational AI platform for building and deploying agents across chat, voice, SMS, WhatsApp, email, and ChatGPT. Founded by Bret Taylor (former Salesforce co-CEO) and Clay Bavor, enabling businesses to create AI agents that handle customer service, support, and revenue-impacting interactions.
Sierra news
Agent OS 2.0 launched
Major platform update introducing unified memory layer (ADP), improved orchestration, and expanded channel support
Voice agents now handle more calls than chats
17 months after voice launch, Sierra's platform handles over 100M+ conversations annually with voice exceeding chat volume
Voice product announced
Sierra launched phone support for AI agents with lifelike voice quality, sentiment detection, and seamless escalation
Public launch announced
Sierra introduced as enterprise conversational AI platform with partners including WeightWatchers, SiriusXM, Sonos, OluKai
Key features
Multi-channel deployment
Build once, deploy everywhere: chat, voice, SMS, WhatsApp, email, ChatGPT, and Live Assist for human agents
Ghostwriter
AI-powered agent builder that creates production-ready agents from SOPs, transcripts, audio recordings, or plain English descriptions
Voice capabilities
Enterprise voice agents with low-latency responses, interruption handling, background noise filtering, accent support, and sentiment detection across 55+ languages
Voice payments
PCI Level 1 compliant card and ACH payment collection entirely over phone without IVR handoff
Agent Studio
No-code visual builder for designing complex agent journeys with tools, integrations, and guardrails
Live Assist
Augments human support agents with real-time guidance, auto-drafted responses, and one-click actions
Agent Data Platform (ADP)
Unified memory layer connecting conversations with business systems for context, continuity, and personalization
Voice Simulations
Test agents against transcription errors, background noise, and speaker variation before live deployment
Integration ecosystem
40+ pre-built integrations plus custom integration framework for connecting to internal and external systems
Agent optimization
Explorer for deep performance analysis, Monitors for proactive issue detection, and Experiments for multivariate testing
Sierra pricing
Outcome-based pricing model with negotiated rates per contract. No public pricing page or self-serve plan. Typically requires enterprise sales engagement.
| Plan | Price | What's included |
|---|---|---|
| Outcome-based (standard) | Custom per contract | Pay for defined outcomes (resolved conversations, saved cancellations, upsells, cross-sells). Unresolved/escalated conversations typically no charge. Some routing calls billed per conversation. |
| Enterprise (AWS Marketplace estimate) | $1,000,000+ per 12 months | Platform access via private offer; additional outcomes at $0.01/unit |
Pros & cons
Pros
- + Single unified agent across all channels with consistent brand voice and policies
- + Enterprise-grade voice quality with natural conversation handling
- + No-code agent building for non-technical teams
- + Outcome-based pricing aligns company incentives with customer results
- + Comprehensive testing and optimization tools (voice simulations, multivariate tests)
- + Strong enterprise security and compliance (PCI L1, deterministic integrations, data governance)
- + Handles enterprise complexity: interruptions, context, escalation, sentiment detection
Cons
- − No public pricing—requires sales engagement to learn costs
- − No free trial or self-serve plan; higher barrier to entry
- − Agent management handled by Sierra team, not fully self-service customization
- − Limited to customer experience use cases; not for internal operations, sales, or admin work
- − Industry estimates suggest $200K–$350K+ first-year cost (not confirmed by Sierra)
Who is Sierra best for?
- • Enterprise customer service organizations managing high conversation volume
- • Companies needing consistent AI agents across voice and digital channels
- • Organizations prioritizing customer lifetime value, retention, and revenue impact
- • Support teams requiring seamless human-AI collaboration
- • Global businesses needing multilingual support (55+ languages)
