
特化型顧客起点のロードマップを支えるエージェント型プロダクト管理システム

Velociti is an AI product operating system that captures customer evidence, turns it into strategy, and dispatches that context to AI coding agents such as Cursor and Claude Code through MCP. It connects discovery, problem and story maps, initiatives, and backlog tickets in one continuous loop.
月間サイト訪問数の推計
このドメインの Similarweb 推計値であり、アクティブユーザー数ではありません。観測データのある月のみ表示し、取得日と対象月を区別しています。
取得日 2026/11/11

編集部による 5 点満点の評価です。ユーザー評価の平均ではありません。 このページの各視点は、製品情報をもとに AI がまとめたものです。実際の利用者のレビューではありません。
OpenAITools.app のテレメトリ(2026-11-11 検証)によると、Velociti(velocitipm.com)は AI プロダクトマネージャーに分類される AI プラットフォームで、月間 1484 の訪問を生み出し、前月比のトラフィック増減は -329(-18.1%)です。主要な地域市場はアメリカ合衆国(トラフィックシェア 100%)で、無料トライアル、有料の料金モデルで運営されています。月間ボリューム別の主な競合代替ツールには Productboard(月間 29.75万訪問)、Olvy(月間 1.43万訪問)、Bagel AI(月間 6804 訪問)が含まれます。
MCP経由でCursorにコンテキストを渡せるのが最高です。
マップの種類が多くて最初は迷います。
サイト検証・料金体系・同カテゴリ比較に基づき AI が多角的な論点を要約した参考視点であり、実在ユーザーの個別投稿ではありません。
Velo AI generates your canvas, problem maps, story maps and initiatives from a short prompt or an existing product document, so the Context Loop starts without blank pages.
Interviews, customer feedback, support tickets, product docs and usage data live in one persistent layer that does not reset every sprint.
Initiatives and the reasoning behind them are delivered to MCP-compatible coding agents such as Cursor or Claude Code, with Jira handling the backlog.
Real-time recommendations highlight gaps in strategy, missing context and the next best action as work moves from discovery through build.
Every initiative links back to the customer evidence behind it and forward to planned delivery, all prioritized against theme-based product strategy.
Velociti is an AI product operating system that captures customer evidence, turns it into strategy, and dispatches that context to AI coding agents such as Cursor and Claude Code through MCP. It connects discovery, problem and story maps, initiatives, and backlog tickets in one continuous loop.
Bring interview notes, support tickets and feedback into one Context Layer, then let Velo AI draft problem maps, story maps and initiatives you can defend with evidence.
Replace ticket-only prompts with Context Dispatches that carry the problem, evidence and definition of done, so agents build against requirements rather than guesses.
Use theme-based strategy and traceable initiatives to confirm that faster shipping turns into adoption instead of a larger pile of unused features.
Turn any initiative into user stories, backlog tickets or a working prototype without re-typing context into other tools.
同じ主要カテゴリの競合 AI ツールをテレメトリで並列比較
| 順位 | AI ツール | 月間訪問数 | 前月比成長率 | 直接流入の割合 | 料金 | 直接比較 |
|---|---|---|---|---|---|---|
| ● | Velociti | 1484 | -18.1% | 直接流入 39% | 無料トライアル、有料 | 表示中 |
| 1 | Productboard | 29.75万 | -9.3% | 直接流入 67% | フリーミアム、無料トライアル、有料、料金は要問い合わせ | vs Productboard |
| 2 | Olvy | 1.43万 | -15.8% | 直接流入 92% | フリーミアム、有料、料金は要問い合わせ | vs Olvy |
| 3 | Bagel AI | 6804 | -38.6% | 直接流入 40% | 料金は要問い合わせ | vs Bagel AI |
| 4 | ChatPRD | 12.88万 | +1.5% | 直接流入 39% | フリーミアム | vs ChatPRD |
| 5 | Monterey AI | 5560 | +42.2% | 直接流入 39% | 料金は要問い合わせ | vs Monterey AI |
| 6 | Samepage | 2484 | +21.1% | 直接流入 41% | フリーミアム | vs Samepage |

特化型顧客起点のロードマップを支えるエージェント型プロダクト管理システム

特化型AIでユーザーフィードバックを管理し、チェンジログで顧客の声を製品判断に変える
特化型散在する顧客の声を収益順のプロダクト判断に変える「プロダクトブレイン」

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