MDLR is an AI-driven, open-source framework designed to transform unstructured content, such as comments and notes, into organized, actionable summaries. Whether it's for personal use or collaborative projects, MDLR adapts to your needs.
MDLR is an AI-driven, open-source framework designed to transform unstructured content, such as comments and notes, into organized, actionable summaries. Whether it's for personal use or collaborative projects, MDLR adapts to your needs.
MDLR is an innovative, open-source framework that utilizes AI to analyze and organize unstructured content like comments and notes. This powerful platform helps transform scattered data into actionable, real-time, and continually evolving summaries. Ideal for personal diaries and collaborative efforts, MDLR provides users with AI-driven summaries that adapt as new data is introduced, ensuring insights remain current and relevant. Easily integrated into various platforms, MDLR enhances project management with auto-updating notes and summaries, perfect for both individual and group usage.
Who will use MDLR?
Project Managers
Team Leaders
Collaborative Teams
Individuals managing personal notes
How to use the MDLR?
Step1: Install the MDLR packages via npm or yarn
Step2: Set up your database, using Supabase as an example
Step3: Integrate MDLR with your platform and initialize your project
Step4: Add and organize your notes
Step5: Use the backend API to generate AI-powered summaries
Platform
web
MDLR's Core Features & Benefits
The Core Features of MDLR
Real-Time Summaries
Modular Component System
Flexible Integration with Supabase
Project Organization
The Benefits of MDLR
Keeps information updated and relevant
Organizes scattered data
Flexible and adaptable to various project needs
Enhances collaboration with real-time insights
MDLR's Main Use Cases & Applications
Personal notes organization
Team collaboration feedback management
Project management efficiency
FAQs of MDLR
When will it be in public access?
The project will begin appearing in modules starting in December 2024.
Under which license is it available?
The project is licensed under the MIT License, allowing flexible use, modification, and redistribution.
Is there a database used for storing and managing data?
We currently use Supabase as an example setup, but the data is not stored on our side. You'll need to roll out your own database.
How can I integrate MDLR into my platform?
You can integrate MDLR using the installation guidelines provided in the documentation, which includes npm/yarn packages and Supabase setup.
What types of projects is MDLR suitable for?
MDLR is suitable for both personal projects and collaborative team efforts, particularly where unstructured feedback needs organizing.
Can I use MDLR commercially?
Yes, MDLR is open-source and available under the MIT License, which allows for commercial use.
What platforms does MDLR support?
MDLR supports web platforms.
How does MDLR ensure the data stays current?
MDLR provides auto-updating summary notes that adapt as new data comes in, keeping your insights fresh and relevant.
What is required for the backend setup?
You will need to create a Supabase table and set up a backend API for generating summaries.
Is MDLR suitable for non-technical users?
While MDLR is designed to be flexible and powerful, some technical setup is required, making it more suitable for users with some technical background.