What is an Initial Dex Offering (IDO)?

Maciej Zieliński

15 Mar 2022
What is an Initial Dex Offering (IDO)?

The development of the cryptocurrency industry and IDO is progressing every year. Thanks to this, new ways of raising funds appear frequently. Initial Dex Offering is one such form. This is one of several ways to raise funds for crypto projects. It is worth noting that the first approach to raising funds for a project's token was the Initial Coin Offering (ICO), which in 2017 brought many advantages and negatives. At the same time, ICO has led to the fact that many investors have become millioners within a few days. How does ICO compare to IDO? Why can IDO be a more interesting concept for raising funds? We are writing about this in thie article below!

ICO and IDO

As we have written earlier, ICO is an unregulated approach to crowdsourcing funds from retail investors. In the crypto space, the main challenges of initial coin offering were related to lack of control and protection of investors' funds. Cryptocurrency projects access was based on complete trust. ICO creators were not due diligence tested. This has led to a time when almost every initial coin offering project could promise significant profits - but these promises have repeatedly proved to be empty.

ICO vs IDO

Many ICO projects have simply proved to be a fraud. Decentralized finance (DeFi) can help with this, as they aim to address this problem through alternative fund-raising models. One such model is the decentralized Exchange (DEX) model. DEX offers cryptocurrency investors access to another, more egalitarian model of crowdfunding in the crypto market.

What is a DEX offer or IDO?

It is worth noting that the original concept of the initial offers of DEX has changed enormously over the years and in its current most popular form has little to do with what it planned to implement at the start of the initial IDO (Initial DEX Offering). In fact, the initial offer of DEX is the successor to initial coin offering and IEO, because its goal is to collect money and launch the project. However, unlike ICO and IEO, in which tokens are sold before being listed, in the case of initial dex offering, they are immediately listed on a decentralized exchanges. For this reason, the name DEX was created.

DEX

What is the Raven Protocol? The first ever Initial DEX Offerings took place in June 2019 – it was called the Raven Protocol. The protocol team selected the decentralized Binance DEX exchange. They place a new token at a specific price, and the traders could buy it until the hard cap has been reached on binance dex. 

In theory, this particular way of fundraising had several powerful benefits, including:

  • Quick Trading
  • Immediate liquidity was achieved
  • An open and transparent means pf collecting money has been achieved

However, investors were not satisfied. The reason was that these symbolic sales would be sold out in a few seconds, leaving a small opportunity for the average investor to participate in the project. As a result of the immediate selling of the entire offer, there was speculation that it was done by bots. This is how the first initial dex offering start platforms, which are gaining popularity today, were formed.

What is a starting offer for DEX and IEO (Initial Exchange Offerings)

The first offer of DEX (IDO) is a way to raise funds that receives investment capital from retail investors. IDO was created to address the shortcomings of the 'traditional' model of cryptocurrency community funding, the initial coin offering. Given that IDO works with DEX, unlike centralized exchange, DEX can be regarded as a decentralized liquidity exchange. Decentralized liquidity exchange and  initial dex offering is the latest model for funding cryptocurrency projects that want to raise funds from investors. However, let us remember that DEX is less scalable than ICO and IEO, and many trading processes are based on DeFi platforms

Token Generation EVENT and decentralized exchange

Today, in its most popular iteration and form, the initial offers of DEX are particularly similar to Initial Exchange offerings (IEO) with some key differences.

  • In the case of IEO, it was an echange which reviewed projects and conducted token sales. With initial dex offering, it is a third-party platform that checks the stock exchange, while token sales themselves take place in a slightly decentralized manner.
  • In theory, anyone can raise funds through IDO (initial dex offerings) using a third-party start platform because everything he or she would have to do is open the pool.
  • The way it works is quite simple. The project is sent to the starter, and if it meets the requirements, it is selected for the initial dex offering. The process itself may vary from one starter to another, but the concept is always the same.
  • There is a pool from which users can buy an "IOU" of the token that the project wants to run. The IOU is a confirmation of the debt. In other words, investors pay for their tokens in advance, but receive them at the Token Generation Event (TGE), which usually takes place very shortly after the IDO itself (usually within a few hours).
  • Once the IDO has been successfully concluded and TGE has started, the token is immediately traded on a decentralized exchange. In most cases, this is the case with Uniswap because the vast number of projects is still built on Ethereum and their tokens are based on the ERC20 protocol standard.

However, other blockchains are also gaining popularity, including Solana, Polkadot and Binance Smart Chain (BSC). Therefore, some projects prefer to run their tokens on them to avoid high network charges in Ethereum. In this case, the token would be listed on a native stock exchange, such as the BSC’s PancakeSwap.

How do IDO cryptocurrencies work?

IDO (initial dex offering) works because DEX can provide instant liquidity for tokens based on smart contracts. That is why DEX tends to reward liquidity pool providers with attractive rewards. Liquidity pools allow DEX to operate without unexpected problems for their users. In order to help trade, most projects provide liquidity to DEX by allocating a part of the funds. This approach has become standard practice. Many projects are also supported by the “Proof of Stake (POS) mechanism. The POS consensus is designed to keep the network secure. But in this case, the mechanism mainly serves to discourage investors from selling tokens too fast. This ensures that investors hold their token capital in their portfolio. In return, they earn rewards for their "participation" in the network. Then, when the project is launched, investors can immediately start trading the token. Investors who have purchased tokens faster can sell them at a higher price when initial dex offerings begins to operate. When the public sale starts, the token value increases.

Fees and smart contracts

In the event of an ecchange, the fees for the performance of the new smart contract are negligible, as the trading pairs provide a high degree of liquidity. Smart contracts help manage the asset token and the liquidity pool. It should be stressed that unlike traditional fund-raising models, IDO can immediately create tokens. In addition, any meaningful IDO project can be qualified to raise funds from retail investors. The same can be said about avoiding the high costs of Initial Exchange Offerings (IEO). Investors do not have to wait long for the desired tokens to appear on the stock exchange. The list usually appears immediately after the initial dex offerings is complete. This time allows investors to make money on their investments much quicker compared to initial coin offering .

Pros and cons of IDO

Like any funding method, IDO has its advantages and disadvantages for project's token, which we have decided to present below:

Pros of IDO

  • Availability - IDO has no procedures that can be associated with IEO. As a result, many people can raise capital without unnecessary bureaucracy.
  • Speed - investors are quickly informed of the arrival of tokens on the stock exchanges and start trading because they have immediate access  to trade. The listing occurs almost immediately after the IDO has ended. Its good for token projects. 
  • Immediate liquidity - in connection with the promotion of PoS, significant capital is leftavailable on the stock exchange, thus improving its liquidity.
  • Transparency - anyone can review token contracts and projects beforehand.

Cons of IDO

  • Verification - the low level of verification leads to many rogue creators who attempt to defraud funds.
  • Competition - it is extremely difficult to participate in IDO because of a huge number of competitors who wish to purchase tokens.
  • Token sharing - most tokens in IDO generally reach the team and private investors first, and afterwards to the rest of the entities.
  • However, IDO still seems to be an attractive form of investment, with little bureaucracy and tempting, significant profits.

Crypto projects offered by IDO are lightning-fast. The initial waiting period for selling tokens at the exchange is short, which allows many people to profit quickly. Unfortunately, these offers are often attractive and, as a result, an average crypto trader may not be able to make the purchase in time, as you will see if do your own research into the matter. Moreover, IDO are not usually present on centralized exchanges, which means that they are also directed towards a smaller group of people. However, IDO is attractive due to the lack of bureaucracy, quick access to funds and the immediate provision of liquidity to the platform.

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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