Tokenization – how to choose the best software development company

Maciej Zieliński

17 May 2021
Tokenization – how to choose the best software development company

On Nextrope Blog we have already looked at the topic of choosing a software house in the article: How to choose a sofware house. The following text we decided to dedicate to all those who are facing the choice of software development company for tokenization. 

Tokenization is one of the fastest growing methods of fundraising. Already today it is used not only by startups in the financial industry, but also by real estate giants and the world's largest banks. Tokenization of alternative assets such as luxury cars or alcohol is also gaining popularity. And in recent months there has been a lot of talk about NFT tokens, which are taking the collectibles markets by storm. 

The tokenization process for an entrepreneur new to the industry may seem extremely intricate, but one thing is certain: it requires an experienced team of developers fluent in blockchain technology to succeed. If you decide to outsource blockchain, how to choose the right software house that is up to the task?

Choosing a software development company for tokenization - key issues

Experience of the team of blockchain programmers

There is no doubt that the programmers employed by a software house should have the highest level of qualifications. A good outsourcing partner will employ people who are not only thoroughly familiar with Blockchain principles and practices, but also have comprehensive knowledge of their application in specific business circumstances. 

Programmers at the company you choose should be proficient in all or most of the following programming languages:

  • C++
  • Scala
  • Python
  • Java
  • Javascript
  • Golang
  • Solidity
tokenization software development

In addition, the Blockchain team should have the skills and knowledge necessary to develop Blockchain networks. Including, for example.:

  • - Blockchain Consensus Algorithms ( PoW, PoS etc.)
  • - Cryptography (asymmetric, symmetric, hash operation) 
  • - Distributed ledgers
  • - Smart contracts
  • - Decentralized applications ( dApps)
  • - Ethereum virtual machine (EVM)
  • - Network systems

What else can a software development company do for you?

Discuss with your blockchain technology provider the scope of services you need.  At Nextrope you can count on technological support, consulting and comprehensive planning of your tokenization strategy. In addition, at your request, Nextrope business team can assist you in the process of writing a White Paper, comprehensively describing all major assumptions of your project. 

The platform we will create for you will be fully tailored to the needs of your company and your objectives. Landing page and admin panel will be fully personalized and intuitive to use. You will have access to all statistics, order data and KYC (Know Your Customer) verification at your fingertips in the most intuitive place. 

Will the project be integrated with KYC/AML

KYC (Know Your Customer) and AML (Anti-Money Laundering) processes are an indispensable part of tokenization. The first refers to the legal procedure, obliging legal entities to identify their customers and obtain true and accurate information required to accept funds during token issuance. The second means taking steps to verify the origin of the funds received. 

It is crucial that the software house you intend to hire has knowledge and experience in integration with KYC and AML. This is the case with solutions offered by Nextrope.

tokenization software development

How proactively is the software development company keeping up with the latest trends?

As we have mentioned more than once on the Nextrope Blog, the pace of tokenization development is extremely fast. Today, the entire world is experimenting with Blockchain technologies to maximize the benefits associated with them. That's why it's important to work with a team of developers who stay on top of innovations in the industry. They are the ones who can help your project succeed. 

What currency will you make the payment in 

There are software houses present in the market basing their rates for tokenization on cryptocurrencies. In a way, this is a tempting solution, especially if you are raising funds in cryptocurrencies. However, there are significant risks associated with it, related to changes in exchange rates. 

If you had agreed to a rate of 1 BTC on the 1st of February this year, but made the payment 11 days later, you would have had to pay an additional $14,407 - that's a nearly 43 percent increase in the initially set price. 

Of course, this can also work the other way around: in certain situations, it will save you up to half the price. However, in an unfavorable turn of events, leverage can consume your entire project. So you're playing roulette-a big event in the cryptocurrency market can actually drown your tokenization.

What happens after the token issue?

Usually, with the end of token issuance comes the end of monitoring from the team providing the technology solutions. Don't let this happen in your case! Take care of the long-term development of your product, as well as community outreach, to continue increasing the capabilities of your tokenization project. 

Nextrope as software development company for tokenization

At Nextrope, we have already conducted a total of ten tokenizations for companies in diverse industries, and we are proud of each and every one of them. In addition, we are proud to have conducted one of the first 30 tokenizations in the world. 

If you are looking for a software house that will become your reliable technology partner in the tokenization process, our experts are ready to help you at any stage of it. After years, we simply know the basics of stunning projects. Let our experience become your success.

Most viewed


Never miss a story

Stay updated about Nextrope news as it happens.

You are subscribed

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
Nextrope Logo

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!