Samepage is an AI product-management workspace where humans and agents discover, plan, build and launch product together. It pulls feedback from your calls, tickets, CRM and internal comms into one inbox, groups repeat requests into scored insights, then lets agents research, spec, prototype and write release notes while you make the calls.
網站月造訪量估算
資料為該網域的 Similarweb 流量估算，不是活躍使用者數。僅顯示有資料的統計月份；擷取時間與流量統計月份分別標示。
擷取於 2026年11月11日
這是編輯給出的評估，滿分 5 分，不是使用者評分的平均值。 本頁的各方觀點由 AI 根據產品資訊歸納，不是真實使用者的評價。
依據 OpenAITools.app 於 2026-11-11 查驗的觀測資料，Samepage（samepage.ai）是收錄於 AI 產品經理助手的 AI 平台，每月產生 2484 次造訪，月流量變化量為 +432（+21.1%）。其主要地理市場為印度（流量佔比 61.7%），並採用免費增值定價模式。依每月流量計算的主要競爭替代方案包括 Productboard（每月 29.75萬次造訪），Notion（每月 1.73億次造訪），Bagel AI（每月 6804 次造訪）。
把一堆 Slack 訊息和 Ticket 整理成精準需求，太神了。
團隊導入需要磨合期。
以下短評基於實時網頁探查、定價機制與同類基準由 AI 綜合生成，用於呈現不同情境下的常見亮點與槽點，非實名真實用戶留言。
Bets reads your calls, tickets, CRM notes and internal comms, groups repeat requests into scored insights, and keeps the supporting evidence attached and up to date.
Assign research, specs or drafts to an agent or a teammate. Work completed by an agent comes back for human review, so nothing ships unchecked.
Two-way sync with Jira, Linear and GitHub keeps issue stages, comments and pull requests aligned between systems, including import of your existing backlog.
Prototype and build directly in your codebase, with coding agents picking up changes and keeping them in sync with the rest of the workflow.
When something ships, release notes, knowledge base updates and ongoing measurement are created in Samepage and pushed to your end systems.
Ask questions across your connected workplace data and get answers that cite where the information came from.
Samepage is an AI product-management workspace where humans and agents discover, plan, build and launch product together. It pulls feedback from your calls, tickets, CRM and internal comms into one inbox, groups repeat requests into scored insights, then lets agents research, spec, prototype and write release notes while you make the calls.
Aggregate feedback from calls, tickets, CRM and chat into a single scored inbox so prioritisation reflects real evidence instead of the loudest voice.
Import the existing Linear or Jira backlog, sync two-way, and let agents research and draft specs for the highest-scoring bets.
Ask questions across connected workplace data and get answers with sources, without manually chasing threads across five tools.
Automate release notes, knowledge base updates and measurement so launches reach customers without extra manual effort.
同一分類下同類 AI 工具的流量並排比較
| 排名 | AI 工具 | 每月造訪次數 | 月增幅 | 直接流量占比 | 價格 | 正面對決 |
|---|---|---|---|---|---|---|
| ● | Samepage | 2484 | +21.1% | 41% 直接流量 | 免費增值 | 目前產品 |
| 1 | Productboard | 29.75萬 | -9.3% | 67% 直接流量 | 免費增值、免費試用、付費、需聯絡報價 | 對比 Productboard |
| 2 | Notion | 1.73億 | +0.1% | 78% 直接流量 | 免費增值 | 對比 Notion |
| 3 | Bagel AI | 6804 | -38.6% | 40% 直接流量 | 需聯絡報價 | 對比 Bagel AI |
| 4 | ChatPRD | 12.88萬 | +1.5% | 39% 直接流量 | 免費增值 | 對比 ChatPRD |
| 5 | Velociti | 1484 | -18.1% | 39% 直接流量 | 免費試用、付費 | 對比 Velociti |
| 6 | Ainna AI | 8351 | +1.1% | 40% 直接流量 | 免費試用、付費、需聯絡報價 | 對比 Ainna AI |
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.
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.
ProdMoh is an AI copilot for product teams that converts raw customer feedback into structured product specs — PRDs, user stories, acceptance criteria and AI guardrails — then pushes that context into coding assistants such as Cursor, Claude and Windsurf through an MCP integration.
ProdMoh is an AI copilot for product teams that converts raw customer feedback into structured product specs — PRDs, user stories, acceptance criteria and AI guardrails — then pushes that context into coding assistants such as Cursor, Claude and Windsurf through an MCP integration.
