AIカスタマーサービスエージェント — チャット・メール・音声を横断してチケットを解決し、測定可能な自動解決率を実現します。
RAGツール利用メモリ音声
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Decagon vs Tofuwhich AI support agent should you pick in 2026?
Conversational support agents that resolve tickets like your best reps.
Tool useMemoryRAG
Autonomous campaign execution across email, ads, and web at brand-safe scale.
Tool useMemoryRAG
Decagon vs Tofu — specs
| Spec | Decagon | Tofu |
|---|---|---|
| Agent Rank | 73 / 100 (A) | 63 / 100 (B) |
| Autonomy | Autonomous | Autonomous |
| Pricing | Subscription · Free tier | Subscription |
| Open source | No | No |
| Capabilities | Tool use, Memory, RAG | Tool use, Memory, RAG |
| Integrations | 3 apps | 5 apps |
| Verified | Verified | — |
| Released | Apr 2025 | Jun 2025 |
Agent Rank breakdown
Decagon
Agent Rank
73/ 100
- 自律性
- 9
- 機能
- 6
- 連携
- 4
- 料金
- 9
- 完成度
- 6
- 検証性
- 10
自律性、機能、連携、料金、成熟度、編集部の検証を基に自動算出。デプロイごとに更新されます。 どのように算出されているか?
Tofu
Agent Rank
63/ 100
- 自律性
- 9
- 機能
- 6
- 連携
- 6
- 料金
- 4
- 完成度
- 7
- 検証性
- 6
自律性、機能、連携、料金、成熟度、編集部の検証を基に自動算出。デプロイごとに更新されます。 どのように算出されているか?
Pros & cons
Decagon
メリット
- +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
デメリット
- −Voice support exists but is not the strength
- −Sales-led — no self-serve sign-up
- −Per-resolution pricing can sting if tickets spike unexpectedly
Tofu
メリット
- +#1 in multiple 2026 marketing-agent buyer guides — top of the vertical
- +Autonomous orchestration across email + ads + web (most agents only do one channel)
- +Strong brand-governance — runs every output through brand library checks
デメリット
- −Enterprise pricing only — no SMB self-serve
- −Newer than Writer/Jasper — fewer Fortune 500 case studies
- −Best ROI requires existing martech stack (HubSpot/Marketo/Salesforce)
Pricing
Decagon
Growth
カスタム
Mid-market
- +Per-resolution pricing
- +Zendesk / Intercom integration
- +Onboarding included
おすすめ
Enterprise
カスタム
Enterprise
- +Custom integrations
- +SSO + audit log
- +Dedicated CSM
Tofu
Growth
カスタム
Mid-market
- +Email + ads + web
- +Brand library
- +HubSpot/Marketo sync
おすすめ
Scale
カスタム
Large brands
- +Unlimited campaigns
- +Multi-brand workspace
- +Advanced governance
Enterprise
カスタム
Fortune 500
- +Custom integrations
- +Dedicated CS
- +Custom SLAs
Which one should you pick?
Decagon
Pick Decagon if cost is the main constraint or if you want a vendor we've verified for accessibility and pricing accuracy.
Try Decagon →Affiliate links. We may earn a commission at no extra cost to you.
Frequently asked
Should I pick Decagon or Tofu in 2026?+
Pick Decagon if cost is the main constraint or if you want a vendor we've verified for accessibility and pricing accuracy. Pick Tofu if its specific capabilities (Tool use, Memory) match what you need. Most working teams running both can use Decagon for primary work and Tofu for the workflows where its specific strengths matter.
What's the price difference between Decagon and Tofu?+
Decagon starts at Subscription · Free tier; Tofu starts at Subscription. 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 Tofu?+
Both Decagon and Tofu are Autonomous agents — neither has a meaningful autonomy advantage over the other. The decision should hinge on capabilities and pricing instead.
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See more alternatives: alternatives to Decagon · alternatives to Tofu
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