aimathはAIを搭載した数学ソルバーで、幅広い数学問題に対して即座にステップバイステップの解答を提供します。基本的な算数から高度な微積分まで、詳細な解説を通じてユーザーの概念理解を助けます。画像から問題を解く写真数学ソルバー機能も備え、学生や教育者にとって多機能なツールです。
Math AIは、GPT-4を搭載したブラウザ拡張機能で、即座にAI数学問題を解決します。数学から物理、化学まで、ブラウザで宿題の問題をスクリーンショットするだけで、正確なステップバイステップの解答を得られます。単に答えを見つけるだけでなく、学生が複雑な概念を理解するのを助けるために設計されています。
製品概要
aimath 製品概要
aimathはAIを搭載した数学ソルバーで、幅広い数学問題に対して即座にステップバイステップの解答を提供します。基本的な算数から高度な微積分まで、詳細な解説を通じてユーザーの概念理解を助けます。画像から問題を解く写真数学ソルバー機能も備え、学生や教育者にとって多機能なツールです。
Math AI 製品概要
Math AIは、GPT-4を搭載したブラウザ拡張機能で、即座にAI数学問題を解決します。数学から物理、化学まで、ブラウザで宿題の問題をスクリーンショットするだけで、正確なステップバイステップの解答を得られます。単に答えを見つけるだけでなく、学生が複雑な概念を理解するのを助けるために設計されています。
Detailed feature comparison
| Feature | aimath | Math AI |
|---|---|---|
| 主要カテゴリー | 宿題ヘルパー | 宿題ヘルパー |
| 追加日 | 2025-08-12 | 2025-08-08 |
| 価格 | フリーミアム | フリーミアム |
| 公式サイト | aimath.com | mathai.online |
| 製品タイプ | ウェブサイト | ブラウザ拡張 |
| Performance data | ||
| ユーザー評価 | 未確認 | 未確認 |
| コメント | 0 | 0 |
| 月間訪問数 | 4.9K | 14.2K |
| 月間成長率 | 14.2% | -5.9% |
| お気に入り | 97 | 107 |
| Details | 詳細を見る | 詳細を見る |
aimath vs Math AI monthly traffic
Compare aimath and Math AI by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the aimath vs Math AI monthly traffic comparison, aimath currently shows 4.9K visits and Math AI shows 14.2K; Math AI has about 2.9 times the visible traffic of aimath, an absolute difference of about 9.3K 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.
aimath monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 12.1K 月間訪問数
- 2026/1: 8.8K 月間訪問数
- 2026/2: 4.7K 月間訪問数
- 2026/3: 3.8K 月間訪問数
- 2026/4: 4.3K 月間訪問数
- 2026/5: 4.9K 月間訪問数
主要地域
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 83.12% | 4.1K |
| 🇮🇳India | 16.88% | 826 |
検索キーワード
Math AI monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 15.6K 月間訪問数
- 2026/1: 22K 月間訪問数
- 2026/2: 16.8K 月間訪問数
- 2026/3: 17.3K 月間訪問数
- 2026/4: 15.1K 月間訪問数
- 2026/5: 14.2K 月間訪問数
主要地域
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 83.35% | 11.8K |
| 🇦🇺Australia | 6.6% | 938 |
| 🇮🇳India | 3.85% | 547 |
| 🇨🇦Canada | 3.38% | 480 |
| 🇵🇭Philippines | 2.82% | 401 |
流入元
| Source type | Percentage | Traffic |
|---|---|---|
| ダイレクト | 92.57% | 13.2K |
| 参照元 | 4.81% | 683 |
| Eメール | 2.62% | 372 |
検索キーワード
Usage comparison
Compare the core capabilities of aimath and Math AI
aimath Core features
Math AI Core features
Use cases
aimath Use cases
Math AI Use cases
aimath vs Math AI:In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth aimath vs Math AI comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. aimath is primarily listed under “宿題ヘルパー”, while Math AI is primarily listed under “宿題ヘルパー”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Product type (aimath: Website; Math AI: Browser extension); Monthly visits (aimath: 4.9K; Math AI: 14.2K); Monthly growth (aimath: 14.2%; Math AI: -5.9%); Favorites (aimath: 97; Math AI: 107); Website (aimath: aimath.com; Math AI: mathai.online). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the aimath vs Math AI monthly traffic comparison, aimath currently shows 4.9K visits and Math AI shows 14.2K; Math AI has about 2.9 times the visible traffic of aimath, an absolute difference of about 9.3K 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 Math AI 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
aimath and Math AI currently overlap in shared categories: 宿題ヘルパー、問題解決、数学; shared tags: AIチューター、教育、宿題のヘルプ、数学ソルバー、ステップバイステップソリューション. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
aimath's unique categories/tags are 代数学、電卓、微積分、幾何学、フォトマス; Math AI's are 学業支援、ブラウザ拡張機能、化学ソルバー、GPT-4、物理ソルバー、学生ツール. 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
aimath has no verified rating, 0 comments, 97 favorites, and 90 likes;Math AI has no verified rating, 0 comments, 107 favorites, and 124 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate aimath first
Put aimath on the priority trial list when the task aligns with “宿題ヘルパー” and especially 代数学、電卓、微積分、幾何学、フォトマス. This follows recorded positioning and does not imply unlisted capabilities are absent.
aimath also currently records: pricing is freemium, product type is website, 4.9K 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 Math AI first
Put Math AI on the priority trial list when the task aligns with “宿題ヘルパー” and especially 学業支援、ブラウザ拡張機能、化学ソルバー、GPT-4、物理ソルバー、学生ツール. This follows recorded positioning and does not imply unlisted capabilities are absent.
Math AI also currently records: pricing is freemium, product type is browser extension, 14.2K 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.
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 aimath and Math AI, 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.




