LabNoteは、研究ワークフロー全体を革新し、効率化するために設計されたAI搭載の研究プラットフォームです。電子実験ノート(ELN)、共同データ管理、AI研究アシスタント(Labnote Scholar)、非臨床文書の自動化(Labnote Preclindoc)などの専門ツールを組み合わせ、研究者が発見に集中できるよう支援します。
Rayyanは、研究者がシステマティックレビューや文献レビューを加速させるために設計されたAI搭載プラットフォームです。自動スクリーニング、重複検出、リアルタイムコラボレーションなどの機能でプロセスを合理化し、研究者のスクリーニング時間を最大90%削減します。80万人以上のユーザーに信頼されており、データインポートから最終報告までのレビューライフサイクル全体をサポートします。
製品概要
LabNote 製品概要
LabNoteは、研究ワークフロー全体を革新し、効率化するために設計されたAI搭載の研究プラットフォームです。電子実験ノート(ELN)、共同データ管理、AI研究アシスタント(Labnote Scholar)、非臨床文書の自動化(Labnote Preclindoc)などの専門ツールを組み合わせ、研究者が発見に集中できるよう支援します。
Rayyan 製品概要
Rayyanは、研究者がシステマティックレビューや文献レビューを加速させるために設計されたAI搭載プラットフォームです。自動スクリーニング、重複検出、リアルタイムコラボレーションなどの機能でプロセスを合理化し、研究者のスクリーニング時間を最大90%削減します。80万人以上のユーザーに信頼されており、データインポートから最終報告までのレビューライフサイクル全体をサポートします。
Detailed feature comparison
LabNote vs Rayyan monthly traffic
Compare LabNote and Rayyan by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the LabNote vs Rayyan monthly traffic comparison, LabNote currently shows 3.4K visits and Rayyan shows 1.1M; Rayyan has about 324.3 times the visible traffic of LabNote, an absolute difference of about 1.1M visits. This reflects visible reach, not feature quality or paid users.
Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.
LabNote monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 6.2K 月間訪問数
- 2026/1: 6.2K 月間訪問数
- 2026/2: 4.7K 月間訪問数
- 2026/3: 6.5K 月間訪問数
- 2026/4: 4.2K 月間訪問数
- 2026/5: 3.4K 月間訪問数
主要地域
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇰🇷Korea, Republic of | 100% | 3.4K |
流入元
| Source type | Percentage | Traffic |
|---|---|---|
| ダイレクト | 100% | 3.4K |
検索キーワード
Rayyan monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 917.4K 月間訪問数
- 2026/1: 942.9K 月間訪問数
- 2026/2: 1M 月間訪問数
- 2026/3: 1.1M 月間訪問数
- 2026/4: 1.1M 月間訪問数
- 2026/5: 1.1M 月間訪問数
主要地域
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 32.99% | 359.1K |
| 🇧🇷Brazil | 31.2% | 339.6K |
| 🇬🇧United Kingdom | 20.31% | 221K |
| 🇵🇰Pakistan | 7.75% | 84.3K |
| 🇵🇹Portugal | 7.75% | 84.3K |
流入元
| Source type | Percentage | Traffic |
|---|---|---|
| ダイレクト | 80.86% | 880.1K |
| 参照元 | 14.66% | 159.6K |
| Eメール | 4.48% | 48.8K |
検索キーワード
Usage comparison
Compare the core capabilities of LabNote and Rayyan
LabNote Core features
Rayyan Core features
Use cases
LabNote Use cases
Rayyan Use cases
Best suited roles
LabNote Best suited roles
Rayyan Best suited roles
LabNote vs Rayyan:In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth LabNote vs Rayyan comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. LabNote is primarily listed under “データ管理”, while Rayyan is primarily listed under “学術”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Primary category (LabNote: データ管理; Rayyan: 学術); Monthly visits (LabNote: 3.4K; Rayyan: 1.1M); Monthly growth (LabNote: -21%; Rayyan: -4%); Favorites (LabNote: 124; Rayyan: 128); Website (LabNote: www.labnote.co; Rayyan: rayyan.ai). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the LabNote vs Rayyan monthly traffic comparison, LabNote currently shows 3.4K visits and Rayyan shows 1.1M; Rayyan has about 324.3 times the visible traffic of LabNote, an absolute difference of about 1.1M visits. This reflects visible reach, not feature quality or paid users.
Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.
If public market visibility is an important first-pass criterion, investigate Rayyan first. The final choice should still follow taxonomy, use case, and a real trial because higher traffic does not prove broader capabilities or better workflow fit.
Product positioning, use cases, and roles
LabNote and Rayyan currently overlap in shared categories: 研究; shared tags: コラボレーション、研究. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
LabNote's unique categories/tags are データ管理、研究室情報管理、AIアシスタント、バイオテック、コンバージョン率最適化、電子実験ノート、ELN、実験室; Rayyan's are 学術、AIスクリーニング、データ分析、重複排除、文献レビュー、医学研究、Prisma、科学執筆. These unique fields are the strongest differentiators: validate the product whose recorded scope matches the task instead of following traffic alone.
What ratings, comments, and favorites can tell you
LabNote has no verified rating, 0 comments, 124 favorites, and 116 likes;Rayyan has no verified rating, 0 comments, 128 favorites, and 116 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate LabNote first
Put LabNote on the priority trial list when the task aligns with “データ管理” and especially データ管理、研究室情報管理、AIアシスタント、バイオテック、コンバージョン率最適化、電子実験ノート. This follows recorded positioning and does not imply unlisted capabilities are absent.
LabNote also currently records: pricing is freemium, product type is website, 3.4K verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
When to evaluate Rayyan first
Put Rayyan on the priority trial list when the task aligns with “学術” and especially 学術、AIスクリーニング、データ分析、重複排除、文献レビュー、医学研究, or the users include 学術的、データアナリスト、司書、医療従事者. This follows recorded positioning and does not imply unlisted capabilities are absent.
Rayyan also currently records: pricing is freemium, product type is website, 1.1M verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
How to validate the recommendation before deciding
The available data describes positioning, public visibility, and community signals, but it cannot prove output quality, speed, integration effort, privacy, or long-term cost in your workflow. Before deciding, run the same representative tasks in LabNote and Rayyan, then record completion time, accuracy, manual corrections, and the real paid threshold. A like-for-like trial turns this comparison into a defensible adoption decision.




