Tokenization will create a new class of alternative assets

Maciej Zieliński

18 Jan 2021
Tokenization will create a new class of alternative assets

We have already covered the tokenization of companies and real estate extensively on the blog. We can also apply similar solutions to alternative assets. Why does it even make sense to tokenize cars, works of art or wine? 

The need for portfolio diversification and the comfort that comes with owning uncorrelated assets are nothing new in the investment world. But it is in times of market stress that their role becomes particularly important. Just look at last summer's record gold price. Alternative assets, however, have far more faces than just metals and precious stones. Cars, art or exclusive liquors not only satisfy people's whims, but can also turn out to be a safe deposit of funds and even bring profits from investments. Why is it worth tokenising them?

Tokenisation of cars

Exotic cars have played an important role in the world of digital content for years. However, anyone who thinks that their only use is to highlight the owner's status is mistaken. Research shows that they can be an extremely worthy investment alternative. According to a Knight Frank report, investment in vintage cars returned over 330% in the 10 years to 2017. Far outperforming other alternative assets such as diamonds, jewellery and art in this regard. However, for obvious reasons, not everyone can afford it. Such a car remains simply too expensive for most. But what if we could only acquire part of it? 

CT1, which is the result of a collaboration between investment platform CurioInvest and digital asset exchange MERJ Exchange, is one of the latest tokens whose value is secured by collector cars. According to both companies, it is the tokenization of luxury goods that will make them accessible to a wider range of investors. 

" If we look at works of art or collector cars we see that they have historically been seen as safe havens for investment, " says Fernando Verboonen, founder and CEO of CurioInvest. " Today they are held by very few. By introducing new technology, we are enabling everyone to fully benefit from the features and functions that define this asset class as a whole."

An investment for everyone

Last year, companies released 1.1 million tokens secured by the $1.1 million Ferarri F12TDF CTI. For less than 4 zlotys we could become shareholders in a supercar worth almost 4 million, whose value in the coming years will probably only increase. The project assumes tokenization of as many as 500 collector cars with a total value of over 200 million dollars. The machines are to be stored and maintained in a garage owned by CurioInvest in Stuttgart. When buying tokens, we do not have to worry about their transport or maintenance. 

Currently, one of the main problems in the secondary sale of exotic cars is the multitude of diverse and complex price models. Often, due to the lack of standardisation and regional differences, no one is able to determine how much a model is really worth. By harnessing the potential of blockchain technology, tokenization will allow the current market value to be adjusted in real time. This will create a number of new opportunities and simplifications, especially in the insurance industry, where it is necessary to accurately determine the value of a car. 

Art

In 2018, sales on the global art market reached $67 billion. Which represents an increase of 6.3% over 2017 and 12% over 2016. For years, post-war and contemporary art has remained the most important sector in terms of value. Over the past 20 years, works from these periods have produced a compound annual return (CAR) that exceeds the S&P's total return by 10.7%. However, the growing art market remains highly illiquid and, like collector cars, accessible only to a limited number of wealthy individuals and institutions. 

Several token projects have recently emerged that seek to change this. The first of these, Maecenas, in 2018 began tokenizing artworks by launching the groundbreaking work of American pop art pioneer Andy Warhol - '14 Little Electric Chairs'.  By basing the sale on blockchain, it was able to attract hundreds of investors previously unconnected to the art world, helping to increase the valuation of the work from $1.7 million to $5.6 million. 

Tokenization significantly increases the liquidity of investment in art - we are trading tokens, only "part" of the work, so we do not have to look for a buyer for the whole. It can also bring numerous benefits to the artist himself. If the artist decides to tokenize his work, he will both earn from the sale of part of the tokens and retain a stake in the whole, allowing him to profit from the increase in value of his work.

Tokenisation of collector wines

Investing in wine for the uninitiated may sound like a weak joke. Nothing could be further from the truth. Collectible wines, as investment assets, are characterised by a high rate of return and significant resistance to economic fluctuations. While the truthfulness of the statement that the older the wine the better is limited - once it reaches full maturity, the quality starts to decrease, there is no doubt that the price of rare examples increases over time.

Source: liv-ex.com

There are a number of factors that guarantee the constancy of this trend. First of all, connoisseurs consider the grape harvest vintage as a factor defining the characteristics of individual bottles, and this vintage is unique - there will not be another 1945 or 2010. 

The growing value of the land on which grapes are grown is also of no small importance. The average price of a hectare of vineyard in the famous Champagne exceeds 1 million euros, which is still a modest amount compared to the 15 million you have to pay for the best Grand Cru in Burgundy. Often, within just one hilltop, there are several parcels with different growing conditions. The differences between them may seem insignificant to the layman, but to the connoisseur they are often colossal. For example, the fruit for the auction record-breaking Domaine de la Romanée-Conti La Romanée Conticomes from a plot of just 1.81 hectares. Demand for rare wines continues to grow (largely due to growing interest in China) while the number of prestigious plots is limited and fixed.

In addition, ongoing climate change and the associated rise in temperature are forcing winemakers in particular regions (e.g. Bordeaux) to change their production processes and even the style of their finished products, potentially increasing the value of older vintages.

Does good wine have to be expensive? 

When it comes to wines that have investment potential this statement is unfortunately completely true. Only about 5% of the wines produced are suitable for ageing, and among these only a small proportion is of real interest to collectors. Of course, it pays to invest not only in the most expensive labels. A few hundred dollars for a bottle of wine, whose price may increase even 4 times over time, does not necessarily sound like an insurmountable barrier for the average investor. It should be remembered, however, that such wine cannot simply be placed on a shelf and wait until its market value increases. Proper storage is key. Temperature, humidity and even lighting - all these determine whether the beverage will actually mature over time and acquire new qualities, or simply spoil. 

Unfortunately, the prices of specialised refrigerators, suitable for storing collectible wines, start at several thousand dollars. Buying and maintaining such equipment with only one bottle in mind simply does not make sense. Not everyone has enough space at their disposal, either. Moreover, wine trading, due to numerous legal restrictions (wine is, after all, an alcoholic beverage), is rarely conducted in the peer-to-peer model, which significantly complicates the matter of its sale by an independent investor. As a result, investments in wine collectors, despite numerous advantages, remain so far closed to a narrow group of people and institutions. As in the case of antique cars and art, this problem can be solved with tokenization.

Tokens as a breakthrough for the industry

When buying tokens whose value would be secured by wine, we would not have to worry about storing the bottles. They would be kept in refrigerators or entire special cellars of the token distributor, just like cars in the garages of the aforementioned CurioInvest. Furthermore, tokenization would significantly increase liquidity in the collectible wine market. When buying wine in the traditional way, we in a way freeze our funds. It often takes years for the value of wine to rise, and even when we decide to liquidate our investments, we have no guarantee that we will find a buyer for our bottle right away. Tokens would be free from such restrictions, we could sell them at any time, without worrying about the cost and risk of transport (bottles are made of glass!) or looking for someone willing to buy the whole wine. 

Source: The World of Fine Wine

Projects distributing such tokens are already emerging. One of them is Vinsent, which, thanks to tokenization, makes it possible to buy cases of wine while it is still in the initial stages of production. The market for exclusive wine during a coronavirus pandemic is characterised by much lower volatility than global stock markets. And as this coincides with a renewed interest in blockchain technology we can expect more similar projects to emerge in the near future.

Where will the tokenization of alternative assets take us?

The tokenization of cars, art or wine does not sound so exotic if we look at already existing projects that have taken even less typical assets for a spin. Take SardineCoin, for example, a token offered by Luxembourg-based MY Sardines, whose value is secured by tinned sardines. The company is banking on the durability and ease of storage of the canned fish, which it says can last for hundreds of years as a collector's item. All indications are that all the possible uses of this technology will be explored for a long time to come. Of course, not every tokenization idea is doomed to success. Not only the characteristics of the assets themselves, but above all the quality of the technological solutions used have a determining influence on the end result. 

Do you have your own idea for a tokenization project? Get in touch with our team of experts who will certainly be able to help you. 

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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

AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

Gracjan Prusik

11 Mar 2025
AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

AI Revolution in the Frontend Developer's Workshop

In today's world, programming without AI support means giving up a powerful tool that radically increases a developer's productivity and efficiency. For the modern developer, AI in frontend automation is not just a curiosity, but a key tool that enhances productivity. From automatically generating components, to refactoring, and testing – AI tools are fundamentally changing our daily work, allowing us to focus on the creative aspects of programming instead of the tedious task of writing repetitive code. In this article, I will show how these tools are most commonly used to work faster, smarter, and with greater satisfaction.

This post kicks off a series dedicated to the use of AI in frontend automation, where we will analyze and discuss specific tools, techniques, and practical use cases of AI that help developers in their everyday tasks.

AI in Frontend Automation – How It Helps with Code Refactoring

One of the most common uses of AI is improving code quality and finding errors. These tools can analyze code and suggest optimizations. As a result, we will be able to write code much faster and significantly reduce the risk of human error.

How AI Saves Us from Frustrating Bugs

Imagine this situation: you spend hours debugging an application, not understanding why data isn't being fetched. Everything seems correct, the syntax is fine, yet something isn't working. Often, the problem lies in small details that are hard to catch when reviewing the code.

Let’s take a look at an example:

function fetchData() {
    fetch("htts://jsonplaceholder.typicode.com/posts")
      .then((response) => response.json())
      .then((data) => console.log(data))
      .catch((error) => console.error(error));
}

At first glance, the code looks correct. However, upon running it, no data is retrieved. Why? There’s a typo in the URL – "htts" instead of "https." This is a classic example of an error that could cost a developer hours of frustrating debugging.

When we ask AI to refactor this code, not only will we receive a more readable version using newer patterns (async/await), but also – and most importantly – AI will automatically detect and fix the typo in the URL:

async function fetchPosts() {
    try {
      const response = await fetch(
        "https://jsonplaceholder.typicode.com/posts"
      );
      const data = await response.json();
      console.log(data);
    } catch (error) {
      console.error(error);
    }
}

How AI in Frontend Automation Speeds Up UI Creation

One of the most obvious applications of AI in frontend development is generating UI components. Tools like GitHub Copilot, ChatGPT, or Claude can generate component code based on a short description or an image provided to them.

With these tools, we can create complex user interfaces in just a few seconds. Generating a complete, functional UI component often takes less than a minute. Furthermore, the generated code is typically error-free, includes appropriate animations, and is fully responsive, adapting to different screen sizes. It is important to describe exactly what we expect.

Here’s a view generated by Claude after entering the request: “Based on the loaded data, display posts. The page should be responsive. The main colors are: #CCFF89, #151515, and #E4E4E4.”

Generated posts view

AI in Code Analysis and Understanding

AI can analyze existing code and help understand it, which is particularly useful in large, complex projects or code written by someone else.

Example: Generating a summary of a function's behavior

Let’s assume we have a function for processing user data, the workings of which we don’t understand at first glance. AI can analyze the code and generate a readable explanation:

function processUserData(users) {
  return users
    .filter(user => user.isActive) // Checks the `isActive` value for each user and keeps only the objects where `isActive` is true
    .map(user => ({ 
      id: user.id, // Retrieves the `id` value from each user object
      name: `${user.firstName} ${user.lastName}`, // Creates a new string by combining `firstName` and `lastName`
      email: user.email.toLowerCase(), // Converts the email address to lowercase
    }));
}

In this case, AI not only summarizes the code's functionality but also breaks down individual operations into easier-to-understand segments.

AI in Frontend Automation – Translations and Error Detection

Every frontend developer knows that programming isn’t just about creatively building interfaces—it also involves many repetitive, tedious tasks. One of these is implementing translations for multilingual applications (i18n). Adding translations for each key in JSON files and then verifying them can be time-consuming and error-prone.

However, AI can significantly speed up this process. Using ChatGPT, DeepSeek, or Claude allows for automatic generation of translations for the user interface, as well as detecting linguistic and stylistic errors.

Example:

We have a translation file in JSON format:

{
  "welcome_message": "Welcome to our application!",
  "logout_button": "Log out",
  "error_message": "Something went wrong. Please try again later."
}

AI can automatically generate its Polish version:

{
  "welcome_message": "Witaj w naszej aplikacji!",
  "logout_button": "Wyloguj się",
  "error_message": "Coś poszło nie tak. Spróbuj ponownie później."
}

Moreover, AI can detect spelling errors or inconsistencies in translations. For example, if one part of the application uses "Log out" and another says "Exit," AI can suggest unifying the terminology.

This type of automation not only saves time but also minimizes the risk of human errors. And this is just one example – AI also assists in generating documentation, writing tests, and optimizing performance, which we will discuss in upcoming articles.

Summary

Artificial intelligence is transforming the way frontend developers work daily. From generating components and refactoring code to detecting errors, automating testing, and documentation—AI significantly accelerates and streamlines the development process. Without these tools, we would lose a lot of valuable time, which we certainly want to avoid.

In the next parts of this series, we will cover topics such as:

Stay tuned to keep up with the latest insights!