Magic is built on top of OpenAI and Hyperlambda, a DSL specifically created to solve anything related to backend software development, and to be the "AI agent programming language". Create full stack apps, in an open source environment, resembling Lovable, Bolt, or Replit. Use natural language as input, and host it on your own hardware if you wish.
No additional "backend connectors" or "database connectors" required!
Everything is 100% integrated, thx to SQLite, with optional MySQL, PostgreSQL, and Microsoft SQL Server capabilities. Below is an app that was created with the following prompt;
Create me a full stack app to manage VIP customer for a car dealership
The whole process took about 30 minutes in total, with less than a handful of errors, correcting the LLM or giving feedback some 5 to 10 times during the process. All bugs were easily tracked down and eliminated by a seasoned software developer during the process.
Magic asked a handful of control questions, before it automatically generated the database, created the backend code based upon the integrated Hyperlambda Generator, before finally assembling the frontend based upon the API - Complete with authentication and authorization, 100% secure (of course!) - You can try it out here. Everything deployed locally, on the integrated and built-in webserver - So no deployment pipelines are required.
- Username is "demo"
- Password is "demodemodemo"
Below is the AI agent in Magic creating the system, 100% autonomously.
In addition to the AI agent in its dashboard, that generates entire full stack apps using nothing but natural language input - There's a whole range of additional components in the system allowing you to automate software development, such as for instance;
- CRUD generator, creating API endpoint using database meta information
- SQL Studio, allowing you to visually design and manage your SQL databases
- Built-in RBAC
- Hyper IDE, for manually edit code in a VS code like environment
- Task manager for administrating and scheduling tasks
- Machine Learning component allowing you to manage AI agents and chatbots
- Plugin repository for installing both frontend types of websites, and backend code
- Plus many more ...
Magic is also a web server, allowing you to instantly deploy everything, without compilation, build processes, complex pipeline connectors, etc. So the process is as follows;
- Create your prompt
- Press enter
- It's in production
In addition to having the ability to generate pure JS, CSS, and HTML frontends, that's immediately being served, without any deployment pipelines - The system also comes with several pre-built frontend systems out of the box, such as the AI Expert System, which allows you to serve password protected AI agents, and/or for that matter deliver entire SaaS AI solutions.
Ths system is particularly well suited for creating AI agents. Below is a screenshot from Hyper IDE.
The above illustrates how Magic facilitates for "comment driven development", as in provide it with a declarative comment, and have the system implement the code.
If you choose to create AI agents instead of full stack app, something the system is particularly well suited for, you can choose to deliver these as password protected AI expert systems, or embeddable AI chatbots, embedded on your website. Below is our AI chatbot. You can try it here
When we measure Hyperlambda and Magic Cloud, it's roughly around 20 times faster than similar solutions built in Python, such as Fast API or Flask. Compared to LangChain, it's probably around 50 times faster, in addition to making it much easier to create workflows, due to being able to create backend code using English. Hyperlambda solutions are in general on pair with C# combined with Entity Framework. Below is Hyperlambda versus Fast API and Flask.
Magic Cloud is built in C# and .Net Core.
The easiest way to get started is to use Docker and create a "docker-compose.yaml" file with the following content;
services:
backend:
image: servergardens/magic-backend:latest
container_name: magic_backend
restart: always
ports:
- "4444:4444"
volumes:
- magic_files_etc:/magic/files/etc
- magic_files_data:/magic/files/data
- magic_files_config:/magic/files/config
- magic_files_modules:/magic/files/modules
frontend:
image: servergardens/magic-frontend:latest
container_name: magic_frontend
depends_on:
- backend
restart: always
ports:
- "5555:80"
volumes:
magic_files_etc:
magic_files_data:
magic_files_config:
magic_files_modules:Save it somewhere, and execute docker compose up or something, visit localhost:5555, login with "root" / "root", and configure the system. You can read more here for alternatives, such as running the codebase directly on your own machine.
The system internally is using OpenAI's GPT-5.2, with some reasoning turned on - But everything is tunable, and you can with a little bit of effort exchange the integrated defaults with Ollama or Hugging Face models. However, the Hyperlambda Generator's training dataset is not made public, and we have no plans to do so either. This means that worst case scenario, you're still running your already generated systems perfectly fine, without the ability to generate new systems - Even if you were to loose the Hyperlambda Generator for some reasons.
The Hyperlambda Generator is however a fairly unique thing, due to Hyperlambda's integrated security model, something that allows for dynamically generating tools on the fly, and securely executing the generated code on the backend. Something demonstrated in our natural language API.
Magic Cloud is built in .Net Core 9, soon upgrading to 10, and its dashboard is Angular. Hyperlambda again was entirely invented and created by yours truly, and you can find some articles about its unique technology below.
However, Hyperlambda, and hence Magic Cloud by association, was built on a unique design pattern called "Active Events", or "Slots and Signals", which is an in-process model for executing "dynamic functions", that's 100% unique for Magic Cloud. Active Events is at the core of Hyperlambda, and completely eliminates 100% of all cross projects dependencies, resulting in 100% "perfect" encapsulation and cohesion.
For instance, polymorphism is implemented at the function invocation level, and not the class or type. I'm so confident in its codebase quality, I'll give you $100 if you can find a (severe security) related bug in its backend!
Although we currently at the moment give away Hyperlambda Generator tokens for free, you still need your own OpenAI API key. You can configure this after having logged in the first time.
Magic Cloud and Hyperlambda is developed and maintained by AINIRO.IO. We offer hosting, support, and software development services on top of Magic Cloud, in addition to delivering AI agents, chatbots, and AI solutions.
This project, and all of its satellite project, is licensed under the terms of the MIT license, as published by the Open Source Initiative. See LICENSE file for details. For licensing inquiries you can contact Thomas Hansen thomas@ainiro.io
The projects is copyright of Thomas Hansen 2019 - 2025, and professionally maintained by AINIRO.IO.