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。
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Decagon vs Sycamorewhich AI support agent should you pick in 2026?
Conversational support agents that resolve tickets like your best reps.
Tool useMemoryRAG
Decagon vs Sycamore — specs
| Spec | Decagon | Sycamore |
|---|---|---|
| Agent Rank | 73 / 100 (A) | 67 / 100 (B) |
| Autonomy | Autonomous | Semi-autonomous |
| Pricing | Subscription · Free tier | Subscription |
| Open source | No | No |
| Capabilities | Tool use, Memory, RAG | Tool use, Memory, RAG, Multi-agent |
| Integrations | 3 apps | 4 apps |
| Verified | Verified | — |
| Released | Apr 2025 | Mar 2026 |
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?
Sycamore
Agent Rank
67/ 100
- 自律性
- 8
- 機能
- 8
- 連携
- 8
- 料金
- 4
- 完成度
- 6
- 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
Sycamore
メリット
- +$65M seed Mar 2026 (Coatue + Lightspeed) — one of the largest agent-platform seeds ever
- +Built by ex-Atlassian CTO — strong execution + enterprise distribution roots
- +Trust + memory layer designed for "production at scale" agents
デメリット
- −Newest of the agent-OS platforms — limited public case studies
- −No public pricing — sales-led motion
- −Competing against Dust, Sema4.ai, Glean for the same enterprise budget
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
Sycamore
Team
カスタム
Engineering teams
- +Agent OS core
- +Standard integrations
- +Standard SLA
おすすめ
Enterprise
カスタム
Large orgs
- +Multi-agent coordination
- +Trust + memory layers
- +Strategic CS
Sovereign
カスタム
Regulated
- +On-prem deployment
- +Dedicated engineering
- +Custom integrations
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.
Try Decagon →Sycamore
Pick Sycamore if its specific capabilities (Tool use, Memory) match what you need.
Try Sycamore →Affiliate links. We may earn a commission at no extra cost to you.
Frequently asked
Should I pick Decagon or Sycamore 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 Sycamore if its specific capabilities (Tool use, Memory) match what you need. Most working teams running both can use Decagon for primary work and Sycamore for the workflows where its specific strengths matter.
What's the price difference between Decagon and Sycamore?+
Decagon starts at Subscription · Free tier; Sycamore 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 Sycamore?+
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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