Sierra
Enterprise AI agents that run customer conversations across chat, voice, email and WhatsApp
Pricing
Paid
Platforms
Web, API
Developer
Sierra AI
Rating
4.6 / 5.0
Last Updated
September 18, 2026
Overview
Sierra is a conversational AI agent platform for customer-facing work, co-founded by Bret Taylor, formerly co-CEO of Salesforce and a member of the OpenAI board, and Clay Bavor, who spent 18 years at Google and most recently led Google Labs.
The company frames its ambition as agents as a service: you describe the outcome you want, and intelligent agents build, execute and continuously improve the work.
In practice that means several distinct products rather than a single chatbot - Ghostwriter, the agent-building agent; Agent Studio for no-code builds; the Agent SDK for code-first teams; Horizon for long-horizon work that plays out over days or months; plus a Context Engine, Insights, Explorer, Channels and Live Assist.
For marketers the interesting part is channel breadth plus memory.
One agent can answer on website and in-app chat, WhatsApp, Apple Business Chat, SMS, email and voice, and Sierra also lists deployment inside ChatGPT.
Voice supports inbound and outbound calls with low-latency conversations that cope with interruption and background noise, detect sentiment in real time and use Voice Personas across 60-plus locales so a brand sounds like itself in every market.
Published demos go well past support and into revenue work: cancellation saves, loyalty and card growth, product recommendations, reservation management and service recovery, while Insights ties performance to CSAT and case resolution with automated tagging, one-click investigation and auditing that shows which knowledge sources and systems an answer came from.
Several things about Sierra are deliberately enterprise-shaped.
Pricing is outcome-based - the site states that you only pay for the value it delivers - and no price list is published, so every engagement runs through a scoped sales process with volume and resolution rates quoted for your use case.
Trust work is public instead: SOC 2, ISO 42001, GDPR, FedRAMP and PCI DSS compliance, alongside a customer roster that includes SiriusXM, Sonos, ADT, Uber, Wayfair, Rivian, Redfin, CarMax, Paychex, Docusign, Discord, nubank, Singtel, SoftBank and Hyatt.
The trade-off is the familiar one for vendor-reported results: resolution and revenue figures on the site come from Sierra and its customers rather than independent testing, and a serious deployment needs CRM, ticketing and knowledge integrations before agents behave correctly.
Teams looking for a free trial and a credit-card checkout should look elsewhere; teams replacing a customer conversation workflow at scale are exactly who this is built for.
Use Cases
Replacing tier-one support conversations across chat, email, SMS and WhatsApp with one agent
Running outbound voice campaigns for renewals, appointment confirmations and lapsed-customer win-back
Saving cancellations by having the agent surface retention offers and loyalty options during the conversation
Personalizing product recommendations and upsells inside service conversations instead of only answering questions
Assisting human support teams with suggested replies, plus auditing and alerting on conversation quality
Who Is This For
Enterprise CX and digital leaders replacing high-volume tier-one support with agents
Retention and loyalty teams that want agents to act on churn signals instead of only answering questions
Global brands needing one agent across many languages and messaging channels, including voice
Telecom, retail, financial services, travel and healthcare organizations with compliance requirements
Product and engineering teams that want an agent platform with both no-code and SDK paths
Key Features
Ghostwriter, the agent-building agent
Build or change agents by describing the behavior you want, or by uploading SOPs, raw transcripts and audio interviews; Ghostwriter generates the journey, runs simulations and diagnoses failures.
One agent, every channel
Deploy the same agent on web and in-app chat, WhatsApp, Apple Business Chat, SMS, email and voice - plus ChatGPT - instead of maintaining separate bots per surface.
Human-sounding voice agents
Inbound and outbound voice with low latency, interruption handling, noise tolerance and real-time sentiment detection, plus Voice Personas tuned across 60-plus locales.
Insights, Explorer and observability
Track CSAT and case resolution, auto-tag conversations, investigate any data point in natural language, and audit which knowledge sources and systems each answer touched.
Enterprise trust and Agent SDK
Code-first teams get an SDK with composable skills such as triage, respond and confirm, while the platform publishes SOC 2, ISO 42001, GDPR, FedRAMP and PCI DSS compliance.
Pros & Cons
Pros
- Outcome-based pricing means you pay for delivered value rather than seats or messages, which aligns the vendor with resolution rates
- One build covers chat, voice, email, SMS, WhatsApp and ChatGPT, avoiding a separate vendor per channel
- Ghostwriter lowers the build cost dramatically for non-technical CX and marketing teams, with simulations and automatic fixes
- Horizon agents act over days or months across systems, which suits long-running journeys like appointment and follow-up coordination
- Public security posture (SOC 2, ISO 42001, GDPR, FedRAMP, PCI DSS) and a roster of large global brands across retail, telecom, financial services and healthcare
Cons
- No published pricing at all - no free tier, no credit-card checkout, and no way to model cost without a sales conversation
- Performance figures come from Sierra and its customers rather than independent testing, so treat resolution and revenue claims as vendor-reported
- Serious deployments need CRM, ticketing and knowledge-base integration, plus governance sign-off, which makes this a project rather than a fast switch
- Agent quality depends on the SOPs and knowledge you feed Ghostwriter; undocumented processes produce weak agents
- Long-horizon agents taking real actions raise governance, audit and escalation questions that smaller teams may not be ready to own
Pricing Plans
Outcome-based deployment
Sierra states you only pay for the value it delivers with outcome-based pricing; rates are quoted per deployment against your conversation volume and resolution profile.
- Pay per resolved outcome
- Chat, voice, email, SMS, WhatsApp and ChatGPT channels
- Ghostwriter, Agent Studio and Agent SDK
- Insights, Explorer and observability
- SOC 2, ISO 42001, FedRAMP, PCI DSS
Multi-market rollout
For global brands running one agent across several languages and markets, with governance and enablement built in.
- 60-plus locales via Voice Personas
- Multi-brand and multi-market deployment
- Auditing, monitoring and alerting
- Implementation and enablement support
- Industry-specific playbooks
Frequently Asked Questions
Editorial Review
Editorial Team
September 18, 2026
Read on sierra.ai on 18 September 2026: pricing is outcome-based, meaning payment is tied to the value delivered rather than to seats or message volume, and there is no published rate card - a deliberate enterprise posture. The product set is unusually complete for an agent platform, spanning Ghostwriter for agent building, Agent Studio for no-code teams, the Agent SDK for engineers, Horizon for work that unfolds over days or months, and Insights and Explorer for measurement and auditing.
Editorial Team
September 18, 2026
Two things kept this at 4.6 rather than higher in our assessment. The first is verification: the CSAT, cost-reduction and revenue numbers on the site are vendor and customer-reported, so they should be treated as claims to validate during a pilot rather than benchmarks. The second is access - with no free tier and no public pricing, the only sane first step is a scoped pilot with agreed resolution definitions, which suits large conversation volumes and is heavy for smaller marketing teams.
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