How much does tokenization cost?

Maciej Zieliński

05 Apr 2022
How much does tokenization cost?

Tokenization is a form of business digitization that is based on blockchain technology. It allows for the creation of tokens or coins and is used to assign their values to a given project. Due to the growth of the cryptocurrency sector and the adoption of blockchain technology, the potential for tokenizing business has increased. Smart contracts enabled full payment automation, which significantly accelerated the process of collecting funds and handling all types of ICO. Why is business tokenization worthwhile? What are the benefits and costs of tokenization? We're writing about it all below!

Tokenization of business

Many business entities are planning to proceed with the tokenization of their business activities. Unfortunately, few people know what the costs associated with this type of action are. In addition, the resulting tokens are often confused with cryptocurrencies. Although both forms are intangible, they use blockchain technology in different ways. Cryptocurrencies have their blokchain, and tokens use out-of-the-box solutions and classic technologies. In addition, it should be noted that tokens can be divided into 3 categories:

  • utility tokens
  • security tokens
  • payment tokens

Many companies use these forms to recapitalize their current business or to start a new business. This brings with it some benefits, but also costs.

What are the benefits and costs of tokenization?

The following is a list of the tangible and intangible benefits of implementing tokenization.

Tangible benefits and potential costs:

  • Legal aspects - Can legal costs save you money on the first day? No, but will it save the issuer and investors many millions of dollars in the event of a large collection? Definitely yes. Tokenization does not need lawyers to assign and link ownership in a project. Tokenization occurs automatically with smart contracts. However, you need to take into account that good tokenization needs to have a meaningful white paper, which often requires technical and legal knowledge. The potential cost of preparing a good white paper starts at $5 000.
  • Blockchain technology — using new technologies to implement your tokenization. We must remember that, depending on the law of the country concerned, additional costs related to the implementation of Know Your Customer (KYC) and AML procedures (prevention of money laundering) may arise. Other costs includes the potential requirements and licenses that are required for trading and collection of digital securities. Such costs are not schematic and may range from a few to several thousand dollars.
  • Automated compatibility — thanks to blockchain technology and smart contracts, we have a wealth of information that cannot be forged. Thus, we save money that we would otherwise have to spend on keeping financial accounting records. Lock-up periods, number of investors, and other policies and regulations may be embedded in or next to digital securities, allowing them to automatically track and enforce the law depending on the jurisdiction. Smart contracts and blockchain technology can save around $150.000 - $200.000 over the span of 5 years of running a business.
  • Time — this is an element which concerns the management’s focus on the tokenization process. Each member managing the project and working in it sacrifices his time and receives remuneration for it. The rates for an hour of a Blockchain Specialist‘s work start at $50. Smart contracts help us save a lot of money, but we need to be aware that implementing tokenization will cost between a few and several thousand dollars in employee remuneration.
  • Administration costs — these are office costs, customer service costs and documentation workflow costs, as well as costs related with any and all formalities. To conduct an ICO, you will need a service that involves organizing financial documents and collecting required licenses. The costs in this case can be between a few and several thousand dollars.
  • Distributions and payments — At the moment, in the case of traditional securities, if a company has to issue a dividend, it passes through transfer agents who usually send checks to investors. The process can be slow and inefficient. The use of blockchain technology allows a registered transfer agent to issue dividends to shareholders immediately with a single click. Additionally, tokenization occurs automatically thanks to smart contacts.
  • The main cost for business tokenization is IT. IT services are the most expensive issue in ICO. The software itself can cost tens of thousands of PLN. On top of that, there are also the costs related to expertise in IT, blockchain and payments. Each project must be individually designed graphically. That is why IT costs are so high.

Intangible benefits and associated costs

Intangible benefits of ICO will mentally help us manage financial collections more efficiently.

By paying the above mentioned ICO costs, we will achieve the following advantages:

  • Saving time – in the case of traditional securities, shares, bonds, etc. the time, money and energy invested in a business system that (in classic business) is slow and bureaucratic are a major problem. Running an ICO in combination with blockchain technology digitizes the whole process, eliminates paperwork and technical problems, and implements automated tools by using smart contracts.
  • Liquidity — The liquidity potential increases in the case of trading on the secondary market after a year, as opposed to waiting for a multi-annual exit, which is typical of traditional private offers. The entire process depends on specific legislation. Moreover, thanks to the market, crypto investors have the ability to trade all around the world 24 hours a day, 7 days a week, with settlements being conducted in a much more efficient and transparent process.
  • Transparency — thanks to public blockchain technology, the investment process becomes much more transparent. All transaction information can be stored on a blockchain. These records protect both the investor and the issuer. Investors can be certain that their data is not compromised at any stage of the ICO. In the case of issuers, shareholder management and non-variable reporting of transactions are available as part of internal control or in the case of any regulatory supervision that may occur.
  • Security — blockchain technology blocks the possibility of counterfeiting and stealing funds. In addition, each transaction is unchangeable and provides decentralized protection of personal data, making the whole process extremely secure.
  • Fractionalisation — While real funds can already be divided into fractions, the current method may be inefficient. Digital securities offer an opportunity to streamline the process of fractionalising assets and revenues generated by them.

Summary

The fixed costs associated with the execution of ICO are significant and can range from tens to more than $100 000. If the project is exceptionally robust, then “sky is the limit” as far as financing the project is concerned. Although initially ICO may seem an expensive solution, over the span of 5 years the costs of running a business may be 40% lower than those generated by using traditional solutions. Since tokenization is still the driving force for generating capital, we believe that the cost and additional benefits will replace the current methods. Blockchain technology has the significant ability to improve the way securities are issued, traded, and managed. As the market matures, the benefits will certainly increase over time. This does not mean that we must or should completely abandon the older processes that exist in today's capital markets. Instead, we can combine these two systems to create effective, efficient and user-friendly solutions for the next generation of securities. ICO can be expensive, but the benefits resulting from it certainly outweigh a simple factor like “finance”.

Tokens are a great solution for many customers. Using blockchain technology ensures increased security. In addition, modern tools, payment technologies and the overal payments industry, as well as solutions such as google pay, apple pay, digital wallets, credit cards and the overall payment network aid with conducting payment tokenization of every project. The payment process itself is incredibly simple and safe. Payment data, sensitive data and recurring payments require the token service provider to conduct payment processing in a professional manner.

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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!