Fellowは、チームや企業向けに設計された安全なAI会議アシスタントです。Zoom、Google Meet、Microsoft Teamsの会議を自動的に録画、文字起こし、要約します。プライバシーを重視するFellowは、あなたのデータがAIモデルのトレーニングに使用されないことを保証します。会議のインサイトを照会するAIチャットボット、CRM連携、50以上のツールとの緊密な統合を特徴とし、会議ワークフロー全体を一元管理します。
製品概要
Fellow 製品概要
Fellowは、チームや企業向けに設計された安全なAI会議アシスタントです。Zoom、Google Meet、Microsoft Teamsの会議を自動的に録画、文字起こし、要約します。プライバシーを重視するFellowは、あなたのデータがAIモデルのトレーニングに使用されないことを保証します。会議のインサイトを照会するAIチャットボット、CRM連携、50以上のツールとの緊密な統合を特徴とし、会議ワークフロー全体を一元管理します。
Radiant 製品概要
Radiantは、会議をキャプチャし、次のステップを自動的に実行するMac向けのAIパーソナルアシスタントアプリです。単なるメモ取りにとどまらず、メール、ドキュメント、チケットなどのアクションを作業ツールで直接提案・下書きし、ボットなしでワークフローを効率化します。
Detailed feature comparison
Fellow vs Radiant monthly traffic
Compare Fellow and Radiant by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the Fellow vs Radiant monthly traffic comparison, Fellow currently shows 187.2K visits and Radiant shows 115; Fellow has about 1,628 times the visible traffic of Radiant, an absolute difference of about 187.1K 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.
Fellow monthly traffic:
Latest traffic
Monthly traffic trend
- 2026/1: 216.4K 月間訪問数
- 2026/2: 197.9K 月間訪問数
- 2026/3: 206K 月間訪問数
- 2026/4: 179.3K 月間訪問数
- 2026/5: 187.2K 月間訪問数
主要地域
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 74.84% | 140.1K |
| 🇨🇦Canada | 6.92% | 13K |
| 🇮🇳India | 6.7% | 12.5K |
| 🇬🇧United Kingdom | 5.95% | 11.1K |
| 🇿🇦South Africa | 5.59% | 10.5K |
流入元
| Source type | Percentage | Traffic |
|---|---|---|
| ダイレクト | 74.94% | 140.3K |
| 参照元 | 23.22% | 43.5K |
| Eメール | 1.84% | 3.4K |
検索キーワード
Radiant monthly traffic:
Latest traffic
Monthly traffic trend
- 2026/1: 36.9K 月間訪問数
- 2026/2: 15.9K 月間訪問数
- 2026/3: 739 月間訪問数
- 2026/4: 0 月間訪問数
- 2026/5: 115 月間訪問数
Usage comparison
Compare the core capabilities of Fellow and Radiant
Fellow Core features
Radiant Core features
Use cases
Fellow Use cases
Radiant Use cases
Best suited roles
Fellow Best suited roles
Radiant Best suited roles
Fellow vs Radiant:In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth Fellow vs Radiant comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. Fellow is primarily listed under “コラボレーション”, while Radiant is primarily listed under “コラボレーション”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Product type (Fellow: Website; Radiant: App); Pricing (Fellow: Freemium; Radiant: Free); Monthly visits (Fellow: 187.2K; Radiant: 115); Monthly growth (Fellow: 4.4%; Radiant: -84.4%); Favorites (Fellow: 81; Radiant: 71). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the Fellow vs Radiant monthly traffic comparison, Fellow currently shows 187.2K visits and Radiant shows 115; Fellow has about 1,628 times the visible traffic of Radiant, an absolute difference of about 187.1K 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 Fellow 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
Fellow and Radiant currently overlap in shared categories: コラボレーション、会議; shared tags: 会議要約、生産性; shared roles: マーケティングマネージャー、プロダクトマネージャー、営業担当者. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
Fellow's unique categories/tags are CRM、プライバシー、AIノートテイカー、コラボレーション、CRM連携、エンタープライズセキュリティ、HIPAA準拠、会議アシスタント; Radiant's are 自動化、タスク管理、行動項目、AI会議アシスタント、ボットレスAI、Macアプリ、議事録、超常的. 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
Fellow has no verified rating, 0 comments, 81 favorites, and 71 likes;Radiant has no verified rating, 0 comments, 71 favorites, and 73 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate Fellow first
Put Fellow on the priority trial list when the task aligns with “コラボレーション” and especially CRM、プライバシー、AIノートテイカー、コラボレーション、CRM連携、エンタープライズセキュリティ, or the users include 最高経営責任者、秘書室長、カスタマーサポート、エンジニアリングマネージャー. This follows recorded positioning and does not imply unlisted capabilities are absent.
Fellow also currently records: pricing is freemium, product type is website, 187.2K 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 Radiant first
Put Radiant on the priority trial list when the task aligns with “コラボレーション” and especially 自動化、タスク管理、行動項目、AI会議アシスタント、ボットレスAI、Macアプリ, or the users include アカウントマネージャー、エンジニア、創業者、プロジェクトマネージャー. This follows recorded positioning and does not imply unlisted capabilities are absent.
Radiant also currently records: pricing is free, product type is app, 115 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 Fellow and Radiant, 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.
比較 FAQ
How should I choose between Fellow and Radiant?
Where does this comparison data come from?
What do unknown fields mean?
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