ChatPRD

ChatPRD is presented as an AI product manager for product teams. According to the page, it can turn rough notes, meeting transcripts, or a single sentence into a PRD grounded in context from connected tools such as Notion, Linear, and Granola. It offers 50+ templates or team-built templates, version history on every document, and a review feature that scores documents on strategy, structure, clarity, and completeness with line-level edits. It also builds clickable prototypes from specs, integrates with tools such as Google Docs, Notion, Linear, Jira, GitHub, and Slack, and offers a hosted MCP server and REST API for coding agents. The page states it is SOC 2 Type II compliant, does not train LLMs on submitted data, and offers SSO, admin controls, and enterprise search for teams. It reports 250,000+ users and a 4.5-star average rating, and says it was created by Claire Vo.

Key features

• Generates product requirement documents from rough notes, meeting transcripts, or a single sentence
• Pulls context from Notion, Linear, Granola, and projects
• 50+ templates, or team-built templates created from a prompt
• Version history on every document
• Document review scoring strategy, structure, clarity, and completeness, with line-level edits
• Publishing suggestions to Google Docs
• Builds clickable prototypes from specs, with revisions kept and sharing by link
• Option to open specs in v0, Lovable, Bolt, or Cursor
• Integrations with Google Docs, Notion, Confluence, SharePoint, Linear, Jira, GitHub, Shortcut, and Slack and Microsoft Teams agents
• Hosted MCP server and REST API for Claude Code, Codex, Cursor, ChatGPT, and other tools
• Shared workspaces, projects, and templates; real-time collaboration and comments for teams
• SSO via Okta, Azure AD, and Google Workspace; admin and usage analytics; enterprise search
• SOC 2 Type II, GDPR and CCPA compliance, and a stated policy of not training on customer data

Best suited for

• Product managers writing PRDs and product docs
• Product teams aligning on specs and templates
• Engineers drafting specs and coding agents reading or editing product docs
• Designers turning research into requirements
• Enterprise teams rolling out an AI product manager with SSO and admin controls

Pricing

Not stated on the website