DeFi – why finance needs decentralization?

Maciej Zieliński

04 Mar 2021
DeFi – why finance needs decentralization?

What is DeFi? In what ways is it better than traditional financial solutions?

DeFi stands for "decentralized finance". It is an umbrella term used to describe the various financial applications of Blockchain technology aimed at pushing financial intermediaries away. Blockchain allows multiple entities to store copies of transaction history, removing it from the control of one central source. This is what decentralization means. 

What is the difference in practice? When you pay by credit card for purchases, financial intermediaries such as your bank or Visa or Mastercard mediate in the transaction between you and the seller, having the right to stop it and register it in their private ledger. With DeFi these institutions disappear.

So what is the advantage of DeFi over traditional solutions?

Advantages of DeFi 

Blockchain = safety 

The use of Blockchain Solution technology provides a new level of transparency and security. In DeFi, every user can see where their digital assets are stored and how they are used. Transaction-securing smart contracts, once implemented, are permanently recorded and cannot be changed. In practice, this means that transactions are only executed if both parties comply with the terms of the contract. 

Exclusive control in the hands of users

Most banks are quickly adapting to the online world, tempting users with new applications or solutions to facilitate transactions such as the Polish Blik. However, the money on user accounts is still under the control of the bank. In this respect DeFi is far ahead. Only the owner has the private key to his decentralized wallet and only he has control over the funds stored there.

Democratization of development

Changes in traditional finance take up to decades, and all decisions from the user's perspective are made behind closed doors. In DeFi, innovations are made in real time, and the development itself reflects the idea of democratizing finance. In DeFi, there are no permissions specifying who can introduce new code to the network, so theoretically it is possible for anyone to do so. Moreover, users of the solutions are often involved in the process of voting on changes. 

DeFi – why finance needs decentralization?
Source: defipulse.com

High return on investment

Traditional banks for the public will continue to be the best place to deposit funds for a long time to come. But in fact, why? After all, interest rates are lowered more and more every year, and fees remain the same. 

In contrast, DeFi financially incentivizes users to bet or borrow assets. The interest that would have gone to the bank when borrowing the customer's money is paid directly to the lender. So with DeFi, the user earns interest that is usually retained by the bank.

DeFi Loans

In fact, in the beginning, all lending was peer-to-peer. People lent funds to each other based on more or less forced trust. For obvious reasons, this arrangement was high risk for the lender. Banks have solved the problems with credit trust, but have added additional costs and levels of regulation. 

Crypto lending allows for a return to a peer-to-peer model. They significantly reduce costs by removing intermediaries while providing complete transaction security. 

DeFi allows peer-to-peer lending to exist directly tailored to borrowers and lenders. Typically, a crypto loan is secured by a smart contract and cryptocurrency assets. The interest rate, on the other hand, is based on the value of the funds that the borrower uses as collateral. The loan can be made in both cryptocurrencies and fiat currencies. 

Support for small entrepreneurs

Lending to small and medium-sized entrepreneurs is one of the most important aspects of traditional finance that needs to change. They are the ones who most often struggle to get funding. Crypto loans are a way to make it significantly easier for them.

The key factor to obtaining such a loan is the amount of cryptocurrency funds that the borrower is able to put up as collateral.  Due to the volatility of cryptocurrencies, loans are very much collateral. In practice, this means that they require a collateral ratio of at least 150%, which provides lenders with some safeguards in managing risk. In contrast, traditional creditworthiness is not considered in the evaluation process.

An example of a solution that provides such support to entrepreneurs is Amplify, which additionally combines another plus of cryptocurrency lending: 24-hour availability. 

DeFi – why finance needs decentralization?
Source: duneanalytics.com

DeFi – what next?

Although DeFi has been on the market for only a short time, it is already a viable alternative to many financial services that have been out there for decades. The growing popularity of DeFi shows that users all over the world want to increase control over their finances and start defining the terms on which they use the services. 

Do you have an idea for a DeFi project? Get in touch with our experts who know exactly how to help you realize it.

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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