insAIght Hub
Because understanding
beats output
Turn scattered AI output into shared understanding — structured, searchable, and easy to act on.
Why insAIght Hub?
Stop losing valuable AI insights in scattered chat logs. Capture, organize, and share knowledge that matters.
Capture Insights
Save valuable AI-generated insights with context, tags, and metadata. Never lose an important discovery again.
Search & Discover
Powerful search across all your insights. Find exactly what you need with tags, full-text search, and filters.
Share Knowledge
Publish insights to your team. Build a shared knowledge base that grows smarter with every contribution.
Create an insight just by asking
No forms, no dashboards. Describe what you want — your agent does the rest.
“Turn our API auth discussion into an insight for developers and tag it auth.”
From Raw Docs to Polished Insights
Watch how insAIght Hub transforms dense technical documentation into beautiful, navigable pages.
# Digest Hub - Product Requirements Document ## Document Info - **Version:** 1.0 - **Created:** 2024-12-29 - **Status:** Ready for Implementation --- ## 1. Overview ### 1.1 Problem Statement AI responses in terminals/chat interfaces are difficult to digest. There is no persistent storage for valuable AI-generated content, and team members can't easily share or reference AI outputs. Creating styled HTML outputs is manual and disconnected from workflow. ### 1.2 Solution Digest Hub is a web application that transforms dense AI/LLM outputs into beautiful, audience-tailored web pages that can be shared across a development team. ### 1.3 Core Concepts - **Digest:** A collection of one or more HTML files... - **DigestFile:** An individual HTML file within a Digest - **Audience:** The target reader type (developer, stakeholder, end_user) that influences how content is presented --- ## 2. Technology Stack | Component | Technology | Version | |-----------|------------|---------| | Language | Ruby | 3.4.5 | | Framework | Ruby on Rails | 8.1.1 | | Database | SQLite | Latest | | CSS Framework | Tailwind CSS | Latest | | UI Components | DaisyUI | Latest | ## 3. Data Models ### 3.1 User ```ruby class User < ApplicationRecord has_secure_password has_many :sessions, dependent: :destroy has_many :digests, dependent: :destroy # Fields: # - id: integer (PK) # - email_address: string (unique, indexed) # - password_digest: string # - name: string # - api_token: string (unique, indexed) # - admin: boolean (default: false) end ``` ## 5. Features & Requirements ### 5.1 User Management (Admin) #### 5.1.1 List Users - Display all users in a table - Show: name, email, admin status, created date - Pagination #### 5.1.2 Create User - Admin can create a user with: email, name, password - Generates API token automatically ... (1,380 lines total)
Left: Your markdown source file with toggle to preview. Right: The polished insAIght page your team will see.
Works with your AI tools
Connect Claude, Cursor, and other MCP-compatible assistants. Your AI reads from and writes to your knowledge base directly — no copy-paste, no context switching.
{
"mcpServers": {
"insaight-hub": {
"url": "https://your-hub.com/mcp"
}
}
}OAuth 2.1 — sign in via your browser. No API tokens to manage.
- OAuth 2.1 — just add the URL, sign in via browser
- Save insights directly from AI conversations
- Let AI search your knowledge base for context
- Works with Claude Code, Cursor, and more
Lean by design — built to save context
When your agent reads an insight, insAIght Hub serves clean markdown — HTML, CSS, scripts, and embedded images stripped out automatically. Your team sees the polished page; your AI gets just the signal. Less context burned, more room to reason.
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Join the waitlist to be first in line when we launch.
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