Builds customer-facing AI agents across chat, voice, email, and messaging.

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What is Sierra?

Sierra is a conversational AI platform for businesses — described on its site as "the leading conversational AI platform for businesses" — that lets companies build and deploy customer-facing AI agents across chat, voice, SMS, WhatsApp, email, and ChatGPT, in 59 languages, available 24/7. It was founded by Bret Taylor and Clay Bavor, who "first met while working together at Google."

Sierra's stated goal is to help businesses "build better, more human customer experiences with AI." Rather than a single chatbot widget, the platform combines agent-building tools (Ghostwriter, Agent Studio), a way to securely connect agents to a company's own systems of record (Context Engine — order management, CRM, and similar systems), and monitoring/optimization tools (Explorer, Insights) so a company can build, observe, and iterate on its own AI agents rather than just turning one on.

Sierra publishes more than 30 named customers on its site, including Rocket Mortgage, Gap Inc., SiriusXM, Uber, Vanguard, SoftBank, and CLEAR, and prices its product with "outcome-based pricing," saying customers "only pay when the software achieves specific, valuable outcomes" rather than publishing fixed plans or per-seat pricing.

Core Features

Ghostwriter

Build or modify an agent by describing how it should behave — prompt workflows, systems integrations, guardrails, tone, and style — with inputs like uploaded SOPs, transcripts, whiteboard photos, and audio recordings.

Agent Studio

The interface for building and managing agents, delivering consistent experiences across voice, chat, email, and WhatsApp in 59 languages, available 24/7/365.

Context Engine

Securely connects the agent to a company's own systems of record — order management, CRM, and similar systems — so it can complete full customer tasks, not just answer questions.

Explorer

Lets a team ask any question in natural language about agent performance; uses analytics and sample conversations to answer it and surface actionable recommendations.

Insights

Built-in testing, automated monitoring, and proactive insights meant to catch conversations that need attention and drive ongoing performance improvement.

Multichannel Deployment with Voice Personas

Deploys a single agent consistently across chat, SMS, WhatsApp, email, voice, and ChatGPT, with distinct Voice Personas for voice channels.

How to Use Sierra

Sierra is built and configured by a company's own team rather than something an individual signs up for and self-serves. Per the company's site:

  1. Describe or show how the agent should behave — Ghostwriter lets a team "build or modify your agent simply by describing how you want your agent to behave," covering prompt workflows, systems integrations, guardrails, tone, and style; inputs can include uploaded SOPs, transcripts, whiteboard photos, and audio recordings, or a plain-English description of the goal.
  2. Connect it to your own systems — the Context Engine securely connects the agent to systems of record such as order management or CRM, so it can carry out full customer tasks rather than just answer questions.
  3. Deploy across channels — a single agent can be deployed consistently across chat, SMS, WhatsApp, email, voice, and ChatGPT, including distinct Voice Personas for voice channels.
  4. Monitor and improve — Explorer answers natural-language questions about conversation performance using analytics and sample conversations, while Insights provides built-in testing, automated monitoring, and proactive alerts to drive ongoing performance improvement.

Use Cases

  • Enterprise customer support and service — the site's published customers include Rocket Mortgage, Gap Inc., SiriusXM, Uber, Vanguard, SoftBank, and CLEAR, spanning finance, retail, media, and mobility.
  • Consistent multilingual, multichannel support — deploying one agent identity across chat, SMS, WhatsApp, email, voice, and ChatGPT in 59 languages instead of building separate bots per channel.
  • Task completion that touches internal systems — using the Context Engine to connect an agent to order management, CRM, or other systems of record so it can resolve full customer requests, not just answer FAQs.
  • Ongoing agent quality management — using Explorer and Insights to analyze conversation performance, run tests, and catch issues, rather than deploying an agent and leaving it unmonitored.

Pros & Cons

Pros

  • Agent behavior is configured by describing intent in plain language, uploaded SOPs, transcripts, or recordings (via Ghostwriter) rather than requiring the team to hand-write conversation flows or code
  • The Context Engine connects agents directly to a company's own order-management/CRM systems so agents can complete real customer tasks, not just answer questions — deployed consistently across chat, SMS, WhatsApp, email, voice, and ChatGPT in 59 languages
  • Publishes more than 30 named enterprise customers across finance, retail, media, and mobility (including Rocket Mortgage, Uber, Vanguard, Gap Inc., and SiriusXM), which is more transparency about real usage than many AI agent vendors offer
  • Outcome-based pricing means a company pays for results the software achieves rather than a flat license, at least as the company describes its own pricing philosophy

Cons

  • No specific pricing numbers are published anywhere on the site — "outcome-based pricing" isn't quantified, so a prospective customer can't estimate cost without contacting sales
  • This is an enterprise platform configured by a company's own team, not something an individual or small team can self-serve and deploy quickly — no sign-up flow or free trial is described on the site
  • The About page doesn't disclose founding year, team size, or funding/valuation, though it does name the founders (Bret Taylor and Clay Bavor) and list office locations (New York, Atlanta, London, Singapore, Tokyo, Paris, Madrid, Toronto, and San Francisco)

Pricing

Frequently Asked Questions