Immutable X alternatives – the best blockchain for your game

Maciej Zieliński

17 Jan 2022
Immutable X alternatives – the best blockchain for your game

Recently, launching an NTF game has become a lucrative investment option. Therefore more and more entrepreneurs seek to find reliable tools that will enable them to launch their own title. Currently, the one created by Immutable and StarkWare seems to be particularly popular. But what are the Immutable X alternatives? 

Table of Contents 

  • Polygon 
  • Immutable X
  • Solana NFT 
  • Scaling solutions for NFT
  • Gas fees 

Polygon 

Immutable X alternatives: Polygon
Immutable X alternatives: Polygon

Polygon, formerly known as the Matic network, is a secure and scalable solution, that uses side-chains of the blockchain to provide faster and cheaper transactions on Ethereum. In many ways, it resembles other Layer 2 projects such as Avalanche and Cosmos, but according to its creators, it is much more efficient and secure. The practice seems to confirm this. 

Ethereum compatible blockchain networks 

Ethereum is the most widely used blockchain protocol, but it has a number of limitations, including:

  • High transaction costs 
  • Low throughput 
  • Problematic UX  

They are a challenge for blockchain products, including NFTs’ ones, especially because they highly decrease scalability. High gas fees and low fees are particularly detrimental for projects where multiple NFTs are regularly minted and traded, as is in the case of NFT games. 

Therefore, many projects are now exploring the use of Ethereum-compatible blockchain networks as a way to mitigate these limitations while leveraging the benefits of the entire ecosystem. Such networks are called Layer 2 solutions. (You can read more about Layer 2 solutions here). Polygon is definitely one of the most promising. 

As a Layer 2 solution, Polygon addresses the diverse needs of developers by providing tools to create scalable dApps that prioritize security, modularity, and UX. This is made possible through a protocol architecture consisting of Proof of Stake (PoS) Commit Chains and More Viable Plasma (MoreVP).

In a nutshell, the operation of the Matic network relies on Commit Chains, which are transaction networks that run on the main blockchain, Ethereum. Commit Chains to combine transactions into batches, which are then confirmed in bulk before returning the data to Ethereum.  

Zero gas fees 

First thing first: On the Polygon network one can mint, buy, and transfer ownership of NFT for free. Yes, that’s right. Quite a great advantage compared to Layer 1 of Ethereum where minting one NFT can cost even more than $100. 

This is particularly important for NFT games, where multiple NFTs are minted and traded. Polygon network can support it at a low cost, without compromising the security or traceability that Ethereum main network provides. 

Furthermore, Polygon’s NFTs can be easily traded ETH tokens. This will be very convenient for your players, as ETH is one of the most popular, and stable cryptocurrencies, which is present on almost every exchange ( both CEXs and DEXs). 

Immutable X alternatives: Solana
Immutable X alternatives: Solana

Solana 

Contrary to the other protocols mentioned in this article, Solana isn’t a Layer 2 solution based on Ethereum. It's a completely different blockchain. 

Launched in 2020 by the Solana foundation, Solana Blockchain aims to solve scaling problems that struggle with most of the contemporary blockchain protocols. Its main objective is to support Defi ecosystem growth by fitting in the so-called blockchain trilemma: decentralization, security, and scalability.

Combining those three factors seems to be the holy grail of the blockchain world. Many projects succeed in supporting one or even two of the factors, but fail when it comes to others. Solana engineers believe that they have implemented all three.

Solana is a third-generation blockchain that, unlike other blockchains, uses a hybrid consensus algorithm. To be more precise, it combines proof-of-history (PoH) with proof-of-stake (PoS). Due to that, it’s able to process over 50,000 transactions per second.

For comparison, Ehereum can’t handle more than 30 at the same time. Now you know why expectations toward Solana are so high.

Another significant problem with Ethereum’s Layer 1 is the gas fee. Gas fees are a pivotal issue for NFT games because minting and trading NFTs on-chain require paying them. Essentially it would be almost impossible to build NFT games only on Layer 1 because running it would be too expensive both for players and creators. And even if it were possible, the circle of potential players would be extremely narrow. Here, again we go back to problems with scalability.

This is why NFT games’ creators seek to find other protocols that will offer lower fees. As we mention, Solana is definitely one of them. It offers almost zero gas fees. What does it mean? Ethereum gas fee can easily go over $100 when on Solana average cost per transaction is only … $0.00025. Without a doubt, that’s a significant difference.  

Minting NFTs on Solana 

Ok, so we have a fast, very promising blockchain with quickly increasing popularity. Why shouldn’t we use it for NFT minting? Many of the recently emerged NFT projects prove that it might be a tremendous idea. 

Thanks to its speed and low fees, Solana is a perfect solution for every NFT project that involves minting and trading a lot of them. Of course, that includes NFT games. But that’s not everything. Using Solana blockchain it would be even possible to perform most of the game’s mechanics on-chain. 

Immutable X alternatives
Immutable X alternatives

Immutable X

Talking about alternatives for Immutable X, we couldn’t forget about … Immutable X . There are good reasons why it’s considered a milestone for playable NFTs. 

Released in April 2021 Immutable X is the first Layer 2 solution dedicated to playable NFT tokens. Even behind its creation stand game’s developers - Australian team Immutable, responsible for the NFT-based card game - Gods Unchained. They aimed to allow for mass adoption of NFT in games

As one of the multiple blockchain systems, Immutable X was built on top of the scaling Layer 2 technology created by StarWare. Thus, the platform became the first Layer 2 solution dedicated to NFT. This allows users to take advantage of the security provided by Ethereum without having to pay gas.

An alternative to using the Ethereum ecosystem could be to create an entirely new, faster blockchain protocol with a different method of obtaining consensus or to develop side chains that process transactions in their own way. However, according to the creators of Immutable X, such solutions would be insufficient, as they would most likely not reach the level of security that Ethereum guarantees. 

It is security that seems to play a key role here: "If security fails, the same thing happens to the authenticity of NFT, and that would have nightmarish consequences." say the platform's developers.

Optimized NFT  creation

One of the biggest advantages of the platform is the Immutable X Mint tool, which allows you to easily and securely create and distribute ERC-721 and ERC-20 tokens. Its biggest advantages are:

- Zero gas fees

- Immediate ability to trade newly created assets

- Same security as the main Ethereum network. 

Launching your own NFT game is a complicated process. Therefore, any help may be useful. Luckily, Immutable X creators are one of the most cooperative in the whole industry.

If you want to launch your own NFT game you can seriously count on them. They will guide you through their solution, provide development consultations, and in some cases even help with marketing campaigns and scaling. 

Completely carbon neutral 

According to its creator, Immutable X aims to become the first completely carbon neutral NFT focused project in the game. 

Immutable X as a Layer 2 solution is far more energy-efficient than Ethereum. Therefore creating NFT on it entails lower carbon emission. Yet, that's not everything. The platform claims that it will buy carbon credits to offset the energy footprint of any NFT on it. They will continue that practice until Ethereums’s Layer 1 will become fully proof-of-stake. 

NFT game development with Nextrope 

Choosing the right technology solutions can be the first step for the tremendous success of your project. However, you should be aware, that launching an NFT game that will attract a global audience will require great skills and knowledge regarding both the technical and business sides of the Blockchain industry. That’s why many projects decide to hire an external blockchain company as a technological partner.

At Nextrope, we can call ourselves pioneers of Blockchain technology in CEE. We conducted one of the first tokenization in the world and since that we keep up to date with the industry. NFT games aren’t an exception. 

Do you want to know how Nextrope’s team can boost your NFT game on a new level? Feel free to contact our specialists who will gladly answer all your questions.

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Master UI Component Creation with AI: The Ultimate Guide for Developers

Gracjan Prusik

24 Mar 2025
Master UI Component Creation with AI: The Ultimate Guide for Developers

Introduction

Modern frontend development is evolving rapidly, and creating UI components with AI tools is helping developers save time while enhancing interface quality. With AI, we can not only speed up the creation of UI components but also improve their quality, optimize styles, and ensure better accessibility.

This article explores how creating UI components with AI is transforming frontend development by saving time and improving workflows. Specifically, we will discuss:

  • Generating components from images,
  • AI for style analysis and optimization,
  • Automatic style conversion and code migration,
  • AI in generating UI animations.

Creating UI Components with AI from Images

One of the interesting applications of AI in frontend development is the ability to generate components from an image. AI can recognize the structure of the interface and generate HTML/CSS or JSX code that matches the provided image. One of the most popular tools for UI creation is Lovable.

For testing, let's see how the tool performs in creating a simple contact form from the page you are currently on, which is Nextrope.

Query:

"Recreate the image I've sent you in Next.js using CSS."

Sample image used in the query:

The result received:

Tworzenie komponentów UI - Wygenerowany widok

Lovable did an excellent job transforming the image into code. The view is fully responsive. It’s important to remember that the more precise the request, the better the AI will replicate the expected view. However, even with a simple command, the tool performed surprisingly well.

Of course, AI has its limitations. It still makes quite a few mistakes. The generated code still requires review and fixes from the developer, but in some cases, the entire process is significantly sped up—correcting the code often takes less time than creating the component from scratch.

Optimizing UI Components with AI Tools for Style Improvements

This problem of inaccurate code reproduction by AI can be partially addressed by using it to analyze and improve styles. Tools like ChatGPT, DeepSeek and Claude are capable of not only generating code but also diagnosing CSS errors and suggesting why a particular style might not be working as expected.

Simple example: Why is the div not centered?

Query: "Why is this div not centered?"

AI analyzes the code and provides the following response:

Problem: The parent container does not have a defined width or display: flex.
Solution: Add the appropriate styles to the parent container.

.parent {
  display: flex;
  justify-content: center;
  align-items: center;
  width: 100vw;
  height: 100vh;
}

AI for Automatic Style Conversion and Code Migration in UI Components

AI can assist with style conversion between different technologies, such as transferring code from traditional CSS to Styled Components or Tailwind CSS.

Let's assume we have a style written in traditional CSS:

.button {
  background-color: blue;
  color: white;
  padding: 10px 20px;
  border-radius: 5px;
  transition: background-color 0.3s ease;
}

.button:hover {
  background-color: darkblue;
}

We can use AI for automatic conversion to Styled Components:

import styled from "styled-components";

const Button = styled.button`
  background-color: blue;
  color: white;
  padding: 10px 20px;
  border-radius: 5px;
  transition: background-color 0.3s ease;

  &:hover {
    background-color: darkblue;
  }
`;

export default Button;

AI can also assist in migrating code between frameworks, such as from React to Vue or from CSS to Tailwind.

This makes style migration easier and faster.

How AI Enhances UI Animation Creation

Animations are crucial for enhancing user experience in interfaces, but they are not always provided in the project specification. In such cases, developers have to come up with how the animations should look, which can be time-consuming and require significant creativity. AI, in this context, becomes helpful because it can automatically generate CSS animations or animations using libraries like Framer Motion, saving both time and effort.

Example: Automatically Generated Button Animation

Suppose we need to add a subtle scaling animation to a button but don't have a ready-made animation design. Instead of creating it from scratch, AI can generate the code that meets our needs.

Code generated by AI:

import { motion } from "framer-motion";

const AnimatedButton = () => (
  <motion.button
    whileHover={{ scale: 1.1 }}
    whileTap={{ scale: 0.9 }}
    className="bg-blue-500 text-white px-4 py-2 rounded-lg"
  >
    Press me
  </motion.button>
);

In this way, AI accelerates the animation creation process, providing developers with a simple and quick option to achieve the desired effect without the need to manually design animations from scratch.

Summary

AI significantly accelerates the creation of UI components. We can generate ready-made components from images, optimize styles, transform code between technologies, and create animations in just a few seconds. Tools like ChatGPT, DeepSeek, Claude and Lovable are a huge help for frontend developers, enabling faster and more efficient work.

In the next part of the series, we will take a look at:

If you want to learn more about how AI is impacting the entire automation of frontend processes and changing the role of developers, check out our blog article: AI in Frontend Automation – How It's Changing the Developer's Job?

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AI in Real Estate: How Does It Support the Housing Market?

Miłosz Mach

18 Mar 2025
AI in Real Estate: How Does It Support the Housing Market?

The digital transformation is reshaping numerous sectors of the economy, and real estate is no exception. By 2025, AI will no longer be a mere gadget but a powerful tool that facilitates customer interactions, streamlines decision-making processes, and optimizes sales operations. Simultaneously, blockchain technology ensures security, transparency, and scalability in transactions. With this article, we launch a series of publications exploring AI in business, focusing today on the application of artificial intelligence within the real estate industry.

AI vs. Tradition: Key Implementations of AI in Real Estate

Designing, selling, and managing properties—traditional methods are increasingly giving way to data-driven decision-making.

Breakthroughs in Customer Service

AI-powered chatbots and virtual assistants are revolutionizing how companies interact with their customers. These tools handle hundreds of inquiries simultaneously, personalize offers, and guide clients through the purchasing process. Implementing AI agents can lead to higher-quality leads for developers and automate responses to most standard customer queries. However, technical challenges in deploying such systems include:

  • Integration with existing real estate databases: Chatbots must have access to up-to-date listings, prices, and availability.
  • Personalization of communication: Systems must adapt their interactions to individual customer needs.
  • Management of industry-specific knowledge: Chatbots require specialized expertise about local real estate markets.

Advanced Data Analysis

Cognitive AI systems utilize deep learning to analyze complex relationships within the real estate market, such as macroeconomic trends, local zoning plans, and user behavior on social media platforms. Deploying such solutions necessitates:

  • Collecting high-quality historical data.
  • Building infrastructure for real-time data processing.
  • Developing appropriate machine learning models.
  • Continuously monitoring and updating models based on new data.

Intelligent Design

Generative artificial intelligence is revolutionizing architectural design. These advanced algorithms can produce dozens of building design variants that account for site constraints, legal requirements, energy efficiency considerations, and aesthetic preferences.

Optimizing Building Energy Efficiency

Smart building management systems (BMS) leverage AI to optimize energy consumption while maintaining resident comfort. Reinforcement learning algorithms analyze data from temperature, humidity, and air quality sensors to adjust heating, cooling, and ventilation parameters effectively.

Integration of AI with Blockchain in Real Estate

The convergence of AI with blockchain technology opens up new possibilities for the real estate sector. Blockchain is a distributed database where information is stored in immutable "blocks." It ensures transaction security and data transparency while AI analyzes these data points to derive actionable insights. In practice, this means that ownership histories, all transactions, and property modifications are recorded in an unalterable format, with AI aiding in interpreting these records and informing decision-making processes.

AI has the potential to bring significant value to the real estate sector—estimated between $110 billion and $180 billion by experts at McKinsey & Company.

Key development directions over the coming years include:

  • Autonomous negotiation systems: AI agents equipped with game theory strategies capable of conducting complex negotiations.
  • AI in urban planning: Algorithms designed to plan city development and optimize spatial allocation.
  • Property tokenization: Leveraging blockchain technology to divide properties into digital tokens that enable fractional investment opportunities.

Conclusion

For companies today, the question is no longer "if" but "how" to implement AI to maximize benefits and enhance competitiveness. A strategic approach begins with identifying specific business challenges followed by selecting appropriate technologies.

What values could AI potentially bring to your organization?
  • Reduction of operational costs through automation
  • Enhanced customer experience and shorter transaction times
  • Increased accuracy in forecasts and valuations, minimizing business risks
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Want to implement AI in your real estate business?

Nextrope specializes in implementing AI and blockchain solutions tailored to specific business needs. Our expertise allows us to:

  • Create intelligent chatbots that serve customers 24/7
  • Implement analytical systems for property valuation
  • Build secure blockchain solutions for real estate transactions
Schedule a free consultation

Or check out other articles from the "AI in Business" series