Company’s tokenization step by step. 8 tips to help you get funding through Blockchain

Iwo Hachulski

06 Jul 2020
Company’s tokenization step by step. 8 tips to help you get funding through Blockchain

Tokenization, by the most popular definition a form of transforming the value of business into digital resources, evokes more and more interest among entrepreneurs. Tokenization may be particularly important for entities that are considering alternative paths to VC or Business Angel to obtain financing for the development of their companies. The post-pandemic crisis and the new reality faced by business founders may encourage them to delve deeper into the subject, especially in the context of scarce funds of traditional investors. The company's tokenization often provides an easier and quicker opportunity to raise funds for further investments. Is this a solution worth considering? Where to start in order to tokenize your business? In this article we present 8 steps to implement the whole process together with specific examples of the tokenized projects.

Preliminary analysis

Make a preliminary analysis to assess your company's financial needs. Specify what you want to raise money for. Identify your target group, competition and market and decide if it is prospective enough. Describe your business or product and consult it with blockchain experts. Answering the question - to whom your issue should be directed - will also allow you to undertake the first analyses related to a later marketing campaign.

Choice of the type of issue and legal form

An important issue is the choice of the type of blockchain tokenization and legal form of the issue. A number of solutions are available, including ICO (initial coin offering), STO (security token offering) and ETO (equity token offering). ICO does not guarantee any ownership rights to the token buyer, and the issue and purchase of the offered tokens can be done almost entirely anonymously. STO and ETO, on the other hand, secure the purchaser through legal solutions, thereby transferring shares in the form of the purchased token. Thanks to the verification of both companies and investors they provide greater security for each party. They are in a way hybrid solutions - a combination of cryptic ICOs with more traditional investment fundraising.

Token economy

The next step is to identify the so-called token economy, which defines the type of emission. It consists of a number of elements:

Define a target, minimum and maximum amount to be collected within the issue. It is important to have an understanding of economic law. Choose the appropriate jurisdiction or law firm that will guide you through the process of establishing a company and a bank account in a given country, taking into account specific administrative requirements. The Nextrope team cooperates with law firms specialising in this area, so you do not have to waste time looking for top-notch lawyers specialising in tokenization.

Decide in which currencies customers can buy tokens. Will they be just cryptic currencies (specify which ones) or will they also be traditional currencies? The most common solutions are ETH, BTC, USDC and USDT. Depending on your preferences, the implementation will be more or less time-consuming.

Companies often lend tokenization on their infrastructure as part of IEO (initial exchange offering). This approach is unfortunately very limited and is not suitable for more legally complicated solutions. The main obstacles for companies considering IEO tokenization are primarily:

- Sharing revenue with another revenue broker.

- Loss of potential to build their own community.

- Problems with handling sensitive data.

Decide within which model the tokens you emit will be functioning. Options include the standard ERC20 or the new ERC1400 format. The first one guarantees that the tokens will not differ from each other in any way. The second one makes the tokens non-fungible. Each of them is unique and marked with a serial number.

Determine the benefits of purchasing your tokens to buyers and how large the token circulation will be on the market.

Start cooperating with a tax and financial advisor, who will develop the most optimal financial constructions for you. At Nextrope we cooperate with many advisors and we will be happy to connect you with them.

KYC/AML

Take care of KYC (Know Your Customer) and AML (Anti-Money Laundering) processes. These are two key elements in the entire tokenization process. The first one is a legal procedure, obliging legal entities (in this case you) to identify their customers and obtain true and accurate information required to receive funds interested in your business. The second one means taking action to verify the origin of the funds received. It is important that the investor platform you plan to use is integrated with KYC and AML service providers. This is the case with solutions offered by Nextrope.

Your needs and expectations

Discuss with your team of specialists what range of services you need. At Nextrope, you can expect not only technological support, but also consultations and preparation of the strategy of the tokenization process. Your platform will be fully personalized for your needs and requirements in relation to the tokenization itself. You will receive a fully customized landing page and an extensive, personalized administrator panel. You will have access to all the statistics, data and KYC verification at your fingertips, in the most intuitive place.

Project's White Paper

Create a fully comprehensive White Paper of your project, based on the advice of the experts' team. Remember to describe the developed token economics in detail. If several dozen pages of the document is a challenge for you, the Nextrope business team is ready to take part in the process of writing the White Paper and help you describe all the most important features of the project.

Marketing Campaign

Once the technical part is ready, develop and start a marketing campaign. Take care of a responsible approach to marketing. Pay attention to the appropriate commission system designed for your customers. Create a loyalty system, withdrawing bonuses to users on the amount paid. Build, motivate and manage your community. Make sure that information about your issue is available on all ICO/STO/ETO listing sites. Participate in industry conferences and focus on publishing your own content and producing industry reports. Showcase the human side of the blockchain-based business by organizing live and video conferences in social media and collaborating with industry influencers.

Further development

Usually, after the issue of your tokens is completed, the monitoring by the team providing technological solutions will end. Do not let this happen to you. Take care of the further development and long term development of your product as well as contact with the community - to continue to expand your business capabilities and resources. Good luck!

Nextrope.com is a software house focused on FinTech solutions market. Our team has already conducted over 10 tokenization processes, both in Poland and abroad. We are happy to help your company with tokenization using blockchain technology. Click here and tell us more about your project.

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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!