Microsoftのオープンソース Multi-agent フレームワーク — 専門化されたエージェント間の会話をオーケストレーションします。
マルチエージェントツール利用コード実行メモリ
LangGraph vs Sycamorewhich AI ops agent should you pick in 2026?
LangChain's stateful multi-agent framework — graph-based orchestration with persistence and human-in-the-loop.
Multi-agentTool useMemory
LangGraph vs Sycamore — specs
| Spec | LangGraph | Sycamore |
|---|---|---|
| Agent Rank | 68 / 100 (B) | 68 / 100 (B) |
| Autonomy | Autonomous | Semi-autonomous |
| Pricing | Free · OSS | Subscription |
| Open source | Yes | No |
| Capabilities | Multi-agent, Tool use, Memory | Tool use, Memory, RAG, Multi-agent |
| Integrations | 3 apps | 4 apps |
| Verified | Verified | — |
| Released | Jun 2024 | Mar 2026 |
Agent Rank breakdown
LangGraph
Agent Rank
68/ 100
- 自律性
- 9
- 機能
- 6
- 連携
- 2
- 料金
- 10
- 完成度
- 7
- 検証性
- 7
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
68/ 100
- 自律性
- 8
- 機能
- 8
- 連携
- 8
- 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
LangGraph
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
LangGraph
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?
LangGraph
Pick LangGraph if cost is the main constraint or if you want the highest autonomy and the verification loop is in place.
Try LangGraph →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 LangGraph or Sycamore in 2026?+
Pick LangGraph 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 LangGraph for primary work and Sycamore for the workflows where its specific strengths matter.
What's the price difference between LangGraph and Sycamore?+
LangGraph starts at Free · OSS; Sycamore starts at Subscription. LangGraph 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, LangGraph or Sycamore?+
LangGraph 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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Adjacent agents in the same category with overlapping capabilities — worth a side-by-side glance before you commit.
役割ベースの自律AIエージェントを協調チームとしてオーケストレーションするオープンソースフレームワーク。
マルチエージェントツール利用メモリDemo · hover to playOpenAIの軽量 Multi-agent リファレンス実装 — ハンドオフとルーティンパターンを採用した教育向けツール。
マルチエージェントツール利用
See more alternatives: alternatives to LangGraph · alternatives to Sycamore
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