I just measure the performance of Lovable versus Magic Cloud, and Magic can do in 3 seconds what Lovable needs 3 minutes to accomplish.

What if I told you that traditional APIs taking input arguments in structured format could be 'obsolete' a couple of years down the road? Well, Natural Language APIs promises to do just that.

If you measure performance of N8N versus Magic Cloud with Hyperlambda, you'll see that Hyperlambda has roughly 7 times better performance.

I just measured the performance of Rust with Actix-Web versus Hyperlambda, and Hyperlambda is 2x faster.

Sha-Hulud is the name of a cyber attack that seems to have started with a Zapier developer machine, now having infected probably all AI software in the world, except ours.

LangChain is the by far most popular Python framework to build AI agents in. However, how does it compare to Magic Cloud with Hyperlambda?

If you measure the performance of Python with Flask, and compare it to Magic with Hyperlambda, you'll realise Hyperlambda has 12 times better performance.

I just conducted a performance test between Hyperlambda and Python's Fast API, and Hyperlambda has 20 times better performance.

With Magic Cloud you can 'generate' a CRM AI agent using no-code, allowing you to have an AI agent dealing with your existing or new CRM

We tested Google's Antigravity AI code generator platform, to see how it performs in comparison to Magic. Here's our rundowm of the differences.

Google just released Gemini 3, and apparently it seems to be 'better' than OpenAI. That's because they're measuring the integration, not the LLM.

Magic Cloud contains a CRUD generator that allows you to generate AI agents connected to your database with no-code.