MDLR

MDLR – AI-Driven Unstructured Content Analytics

MDLR is an open-source framework that analyzes unstructured content—comments, notes, and more—to organize scattered data into actionable, evolving summaries. It adapts to your needs for personal or collaborative projects, delivering AI-driven summaries that auto-update as new data arrives.

Overview

• Purpose: Convert scattered feedback and ideas into living, reviewable summaries.
• Approach: Real-time, auto-updating insights that stay fresh as data changes.
• Access: Designed to be integrated as an extension into your platform to transform unstructured content into intelligent, actionable insights.

How It Works

• Ingest unstructured data such as comments, notes, and ideas.
• Generate concise, evolving summaries that update automatically when new content is added.
• Provide a flexible integration point to embed MDLR into existing platforms for personal or collaborative use.
• Emphasize control over AI-driven summaries, aligning with your workflow and data governance needs.

Quickstart

• Quickstart Shoot a letter 💌
• The project aims to help you begin using MDLR with practical examples and starter setups.

Roadmap & Access

• Public access: The project will begin appearing in public modules starting in December 2024.
• Hosting: Available on GitHub with comprehensive documentation for setup and usage.

Licensing & Data Handling

• License: MIT License, allowing flexible use, modification, and redistribution, including commercial use.
• Data storage: Data is not stored on the MDLR side. You deploy your own database to store and manage project data (example setup uses Supabase).

Use Cases

• Personal knowledge management: Convert scattered notes into evolving summaries.
• Team collaboration: Aggregate comments and decisions into dynamic project summaries.
• Project reviews: Maintain up-to-date review notes as discussions evolve.

Legal & Privacy

• You control data storage and processing by using your own database setup.
• Ensure compliance with your organization’s data governance policies when integrating MDLR.

Getting Involved

• MDLR team encourages feedback and early participation as the project evolves toward broader public access.

How to Use MDLR

1. Integrate the MDLR extension into your platform.
2. Ingest unstructured content from comments, notes, and other sources.
3. Let MDLR generate evolving summaries and review them in real time.
4. Connect to your database (e.g., Supabase) to store and manage project data locally.

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Feature List

• Real-time, auto-updating summaries for unstructured content
• Open-source MIT-licensed framework for flexible use
• Integration as an extension to transform scattered content into actionable insights
• Supports personal and collaborative project workflows
• Deployable with your own database (example: Supabase) to ensure data sovereignty
• GitHub-hosted with comprehensive setup and usage documentation
• Clear roadmap for public access starting December 2024