Agentforce vs Decagon
A side-by-side comparison of Agentforce and Decagon, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
Agentforce
AgentSalesforce's platform for building and deploying autonomous AI agents.
View AgentforceAt a glance
| Attribute | Agentforce | Decagon |
|---|---|---|
| Category (differs) | Agent | Support |
| Pricing | PAID | PAID |
| License | Proprietary | Proprietary |
| Deployment | Cloud | Cloud |
| Platforms | Web, API | Web, API |
| Model support | Multi-model | Multi-model |
| Vendor (differs) | Salesforce | Decagon |
| Capabilities (differs) |
|
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The honest brief
Agentforce
Agents are natively grounded in Salesforce CRM data and Data Cloud via the Atlas Reasoning Engine — turnkey for existing Salesforce shops.
- Prebuilt service and sales agents
- Enterprise guardrails via Einstein Trust Layer
- Large partner and integration ecosystem
- Most valuable inside the Salesforce ecosystem
- Per-conversation pricing can scale costs
- Setup and governance are enterprise-complex
Decagon
Prices per conversation or resolution, not per seat, and lets ops teach agents via natural-language procedures.
- Outcome-based pricing
- Ops author logic, engineers keep guardrails
- Chat, email, and voice
- Takes actions, not just answers
- Enterprise sales-only
- Setup and tuning required
- Model choice abstracted away
When to pick which
We found no distinguishing difference between Agentforce and Decagon on the signals we track — pricing, license, platforms, and model support. Their capability lists differ only in recorded depth — compare them above. Pick on team fit.