Sierra AI Agents

What it does

Sierra AI Agents is a conversational AI platform for businesses. Teams describe a goal in plain English or upload materials such as SOPs, transcripts, whiteboard photos, and audio recordings, and the Ghostwriter tool builds a multilingual, multichannel agent with guardrails. The agent connects to systems of record such as order management and CRM so it can complete tasks like returning an order or processing a claim.

Once deployed, one agent can run across chat, SMS, WhatsApp, email, voice, and ChatGPT. Companion tools analyze performance: Explorer answers questions about conversations, Monitors flag conversations needing attention, Experiments run multivariate tests, and Observability shows tool calls and latency. Memory and outcome optimization are described for tailoring interactions over time.

Sierra suits businesses running customer service or customer experience operations across several channels. Teams can build from written procedures and other materials, then test and refine the resulting agent before connecting it to live systems. Commercial arrangements use outcome-based pricing, so the definition of a billable outcome matters. Confirm those terms, data access and escalation rules during onboarding. Generated behavior and reported results should be evaluated against the organization’s own customer scenarios.

What it can do

• Build conversational agents from plain-English goals or uploaded SOPs, transcripts, and recordings using Ghostwriter
• Deploy one agent across chat, SMS, WhatsApp, email, voice, and ChatGPT
• Connect agents to systems of record such as order management and CRM for end-to-end tasks
• Analyze conversations with Explorer, flag issues with Monitors, and run Experiments
• Inspect agent behavior with Observability covering tool calls, knowledge lookups, and latency
• Use Horizon for long-horizon planning and proactive engagement triggered by real-world signals

Works with

• Systems of record such as order management and CRM (general, not individually named)

Example workflows

Build a support agent from documents

Illustrative example. Inputs: SOPs, call transcripts, and whiteboard photos. Steps: upload materials to Ghostwriter, describe the goal, review the generated agent and guardrails. Output: a multilingual agent ready for multichannel deployment.

Review agent performance

Illustrative example. Inputs: live conversation history. Steps: ask Explorer a question in natural language, review Monitors flags, and check Observability traces for tool calls and latency. Output: recommendations and identified conversations needing attention.

Before you choose

• Agree on the definition and measurement of billable outcomes before signing.
• Review data permissions, customer-action boundaries and escalation paths.
• Validate the agent against your own scenarios and monitor its live performance.

Listed under

• Support
• Chat and email agents
• Voice and phone agents
• AI agents
• Conversational AI
• Conversational-AI
• Customer experience
• Customer-experience
• Customer service

Get started

Use the product page to discuss the intended use case and onboarding.

1. Contact Sierra to discuss the customer workflows and systems involved.
2. Provide approved procedures and knowledge sources, then configure actions and human escalation.
3. Test representative conversations and review outcomes before widening deployment.

Sierra describes outcome-based pricing. Confirm billable outcome definitions, rates, volume commitments and implementation terms for the deployment.

Sierra AI Agents doesn’t publish prices. You get a quote by contacting sales. See their pricing page ↗

Sources for this overview

Product pages, documentation, and pricing checked 29 Oct 2026. Each source supports part of the overview; availability and prices can change.

• Better customer experiences | Sierra ↗sierra.ai
• Product overview | Sierra ↗sierra.ai

Company website

sierra.ai: product, pricing and policy pages

YC directory mirror

Batch and company name

Social accounts

Accounts the company links, and its posts on X

Human review

Checked by a person

knowledge_base

Last checked 29 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.