Decagon vs Sierra
A side-by-side comparison of capabilities, autonomy, integrations, and pricing to help you choose.
Short answer: choose Decagon if you want enterprise ai agents that resolve customer support end to end (Supervised agent, enterprise); choose Sierra if you want conversational ai agents for customer experience (Supervised agent, enterprise).
| Decagon | Sierra | |
|---|---|---|
| What it is | Enterprise AI agents that resolve customer support end to end | Conversational AI agents for customer experience |
| Type | agent | agent |
| Autonomy | Supervised agent | Supervised agent |
| Pricing | enterprise | enterprise |
| Best for | enterprise, mid-market | enterprise, mid-market |
| Deployment | saas, api | saas, api |
| Modalities | text, voice, email | text, voice |
| Models | model-agnostic | model-agnostic |
| Protocols | function-calling, rest-api | function-calling, rest-api |
| Integrations | Zendesk, Salesforce, Intercom, Slack | Salesforce, Zendesk, Stripe |
| Capabilities | 3 documented | 3 documented |
Decagon
- +High autonomous resolution on common request types
- +True omnichannel: chat, email, and voice
- +Well funded and rapidly growing, low vendor-risk for enterprises
- -Enterprise-only with no public self-serve pricing
- -Aimed at high-volume brands; overkill for very small teams
Sierra
- +Strong founding team and enterprise traction
- +Voice and chat in one platform
- +Emphasis on guardrails and measurement
- -Enterprise-only, contact-sales
- -Less suited to small or self-serve teams
Which should you choose?
Decagon is enterprise ai agents that resolve customer support end to end, best for enterprise, mid-market. Sierra is conversational ai agents for customer experience, best for enterprise, mid-market. The right choice depends on the autonomy level you want, your existing integrations, and your budget, all compared above.