Agent IA de service client — résout les tickets via chat, e-mail et voix avec des taux de ticket deflection mesurables.
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Decagon vs Dustwhich AI support agent should you pick in 2026?
Conversational support agents that resolve tickets like your best reps.
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Decagon vs Dust — specs
| Spec | Decagon | Dust |
|---|---|---|
| Agent Rank | 73 / 100 (A) | 77 / 100 (A) |
| Autonomy | Autonomous | Semi-autonomous |
| Pricing | Subscription · Free tier | Subscription · from $29 |
| Open source | No | No |
| Capabilities | Tool use, Memory, RAG | Tool use, Memory, RAG, Multi-agent |
| Integrations | 3 apps | 5 apps |
| Verified | Verified | — |
| Released | Apr 2025 | Mar 2025 |
Agent Rank breakdown
Decagon
Agent Rank
73/ 100
- Autonomie
- 9
- Capacités
- 6
- Intégrations
- 4
- Tarification
- 9
- Maturité
- 6
- Vérifiabilité
- 10
Calculé automatiquement à partir de l'autonomie, des capacités, des intégrations, de la tarification, de la maturité et de la vérification éditoriale. Mis à jour à chaque déploiement. Comment est-ce calculé ?
Dust
Agent Rank
77/ 100
- Autonomie
- 8
- Capacités
- 8
- Intégrations
- 10
- Tarification
- 7
- Maturité
- 7
- Vérifiabilité
- 6
Calculé automatiquement à partir de l'autonomie, des capacités, des intégrations, de la tarification, de la maturité et de la vérification éditoriale. Mis à jour à chaque déploiement. Comment est-ce calculé ?
Pros & cons
Decagon
Pour
- +Chat-first agent with consistently 65–75% tier-1 deflection in production
- +Deep integration with existing helpdesks (Zendesk / Intercom / Salesforce)
- +Mid-market priced — easier conversation than Sierra
Contre
- −Voice support exists but is not the strength
- −Sales-led — no self-serve sign-up
- −Per-resolution pricing can sting if tickets spike unexpectedly
Dust
Pour
- +"Multiplayer AI" — shared, governed workspaces designed for company-wide use
- +$40M Series B (Sequoia, Snowflake, Datadog) signals strong enterprise validation
- +Deepest connector library among agent platforms (Slack/Notion/GitHub/Salesforce/GDrive)
Contre
- −French roots — strongest support in EU/UK time zones
- −Higher per-seat pricing than Glean for read-only retrieval use cases
- −Custom agent authoring requires technical user (less low-code than Gumloop)
Pricing
Decagon
Growth
Sur mesure
Mid-market
- +Per-resolution pricing
- +Zendesk / Intercom integration
- +Onboarding included
Recommandé
Enterprise
Sur mesure
Enterprise
- +Custom integrations
- +SSO + audit log
- +Dedicated CSM
Dust
Free
Gratuit
Individuals
- +1 workspace
- +3 agents
- +GPT-4o + Claude 3.5
Recommandé
Pro
$29/siège/mois
Teams
- +Unlimited agents
- +All integrations
- +Custom data sources
Enterprise
Sur mesure
Large orgs
- +SSO + audit
- +Custom retention
- +Dedicated tenants
Which one should you pick?
Decagon
Pick Decagon if cost is the main constraint or if you want the highest autonomy and the verification loop is in place.
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Frequently asked
Should I pick Decagon or Dust in 2026?+
Pick Decagon if cost is the main constraint or if you want the highest autonomy and the verification loop is in place. Pick Dust if its specific capabilities (Tool use, Memory) match what you need. Most working teams running both can use Decagon for primary work and Dust for the workflows where its specific strengths matter.
What's the price difference between Decagon and Dust?+
Decagon starts at Subscription · Free tier; Dust starts at Subscription · from $29. Decagon is the cheaper entry option. For team deployments the TCO can differ — use the AI Agent Rank TCO calculator for your specific volume.
Which is more autonomous, Decagon or Dust?+
Decagon is the more autonomous of the two (Autonomous vs Semi-autonomous). Higher autonomy ships throughput faster but requires verification loops in place — see our autonomous-vs-copilot framing for when each tier wins.
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Tool UseMemoryVoixRAGAgent IA basé sur la résolution, intégré à Intercom — vous payez uniquement ce qu'il résout réellement.
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