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.
This comparison is generated from the sourced Decagon and Sierra profiles. Open either profile to review its evidence and last-reviewed date.