Decagon vs Sierra (2026)

What sets it apart Agent Operating Procedures: natural-language workflow definitions that support teams author to control agent behavior without engineering tickets

Best for Consumer-facing enterprises automating high-volume customer support across chat, email, and voice while retaining human escalation · Pricing model Custom enterprise pricing quoted through sales, billed on usage. Two options: a fixed rate per incoming conversation, or a higher rate per fully resolved conversation with no charge for escalations. No free tier and no publicly listed price.

Founded in 2023, Decagon operates AI agents that resolve customer support conversations across chat, email, and voice, handing off to human staff when a request falls outside their scope. The distinguishing piece is Agent Operating Procedures: natural-language workflow definitions that support teams write to shape agent behavior without routing changes through engineering. Pricing is quoted through sales on a usage basis, billed either per conversation or per resolution, and there is no free tier. It is aimed at consumer-facing enterprises in sectors such as retail, financial services, travel, and health.

Sources Decagon homepage (product, channels, AOPs, Watchtower, target industries) · Decagon blog: Pricing the AI Agent Economy · Microsoft for Startups: Decagon building the AI concierge

What sets it apart Outcome-based pricing: customers are charged when an agent achieves a defined result (a resolved conversation, a saved cancellation), and unresolved conversations usually carry no charge, in contrast to seat- or conversation-based licensing

Best for Large enterprises in sectors like financial services, telecom, healthcare, travel, and retail that want AI customer-service agents to complete transactions end-to-end and prefer paying per resolved outcome over per seat · Pricing model No published pricing; enterprise sales only. Core model is outcome-based, billing on completed outcomes such as resolved conversations, saved cancellations, and upsells, with unresolved conversations typically not charged; some interaction types (e.g., routing or greeting) can use per-interaction consumption pricing. Deployments generally involve separate setup and integration fees. The DB "starting_price=$0/mo" and "free_tier=false" are consistent with there being no self-serve list price rather than a genuine free entry point.

Founded in 2023 by Bret Taylor and Clay Bavor, Sierra builds AI agents that enterprises deploy for customer service across voice, chat, email, and WhatsApp; the agents connect to backend systems such as CRM and order management so they can complete a task like processing a return or filing an insurance claim rather than only answering questions. Its distinguishing choice is pricing: customers are billed on outcomes, paying when an agent resolves a conversation or saves a cancellation, and in most cases owing nothing when a conversation goes unresolved. Sierra does not publish rates and sells through enterprise contracts that generally include setup and integration work, so it fits large organizations with the backend complexity and budget to justify a custom deployment.

Sources Sierra - Product overview (vendor) · Sierra - Outcome-based pricing for AI Agents (vendor blog) · TechCrunch - Bret Taylor's Sierra raises $350M at a $10B valuation · Featurebase - Sierra AI Pricing 2026