DeFi app – how to build a successful application

Maciej Zieliński

02 Feb 2021
DeFi app – how to build a successful application

Decentralised apps are winning the hearts (and wallets) of users around the world. But despite their growing popularity, the process of launching them remains fraught with challenges and obstacles. What do you need to know before you start working on your DeFi application project? What are the most common mistakes?

The implementation of DeFi applications requires specialist knowledge and a range of diverse skills. A deep knowledge of the decentralized finance market and a team proficient in Blockchain technology are the absolute foundation. 

At Nextrope, we have a track record of working with a number of DeFi projects for which we have created numerous successful solutions in the market. Based on our experience, here is everything you need to know to build a successful DeFi App. 

How to build a Defi application ?

What you need to keep in mind when planning a successful DeFi project:

  • Contact with the target group
  • Speed of project development 
  • Experienced development team
  • Thorough analysis of business logic
  • Integration with other DeFi apps
  • Refined UX Design 

Contact with the target group

It is important to accurately define the target audience of your DeFi app. This will help you not only in planning your project, but also in testing it for UX optimization. Try to catch up with people who might be interested in developing your solution. Their thoughts, comments and insights on using your app will be extremely valuable. Social media such as Twitter, Facebook or even LinkedIn mare great for this purpose. 

Additionally, building a community around your project before it's even launched will make it easier to market and limit the migration of users to other applications.

Speed of project development

The DeFi market is developing extremely dynamically, so the goal of every project is to deliver a new solution in the shortest possible time. Significant delays may lead to the fact that the competition will overtake us. 

In our experience, the optimal duration of a project is 3-5 months. It is extremely important to divide it wisely between three basic stages: planning, development and testing.

DeFi application

A team of experienced programmers

The implementation of a DeFi app project requires a wide range of skills related to the use of the sublime technology that is Blockchain. That is why an experienced and proven team of developers is your key to success. Be sure to read the article on how to choose the right software house.

Make sure that the competence of the people you want to entrust your project to is impeccable, especially in the following areas:

  • Creation and development of smart contracts
  • DAO
  • UI i UX
  • Project testing

Thorough analysis of business logic

Even a brilliant idea based on the best technology stack can fail if the business analysis done at the start is inaccurate. Remember, your application will not succeed if it does not meet the following conditions: 

  • represents a new and interesting solution in the decentralised financial market
  • it is more profitable than other DeFi applications

Make sure that your analysis takes them into account and accurately describes the plan for their implementation. From the technological side, the implementation of these assumptions should be described in detail in the SRS - software requirements specification, which will be presented to you by the outsourcing service provider.

In Nextrope you can count not only on the highest quality programming services, but also on business and technology consulting based on the experience gained during the implementation of dozens of projects. So by developing DeFi app with us you can be sure that its development will look exactly as you need it to. 

DeFi application = the need for integration

Today, DeFi apps are unable to operate in isolation from each other. The world of DeFi apps is becoming a gigantic, branching ecosystem where projects either compete with each other or are connected to each other. This is due to the needs of the users themselves, who expect to be able to sync and move seamlessly between apps, and after all, it is for them that you optimize your project. 

Integration is a complex issue, so it is crucial to allocate sufficient resources and time at the planning stage. Typically, the integration process starts with working with market giants such as Compound, Aave or Curve.fi. These protocols have diverse interfaces and functions, so the developers you hire should have extensive experience not only in creating code, but also in reading it. 

DeFi application

Refined UX 

Your app may even move mountains, but if it is difficult and unintuitive to use, its user base will remain extremely narrow anyway. A well-thought-out and well-designed UX is the basis of modern financial applications.

We understand this very well at Nextrope, which is why in our team, next to Back End specialists, there are Front End programmers and experienced UX designers. 

Building the DeFi application - summary

Creating a DeFi app requires in-depth knowledge not only of technology, but also of finance and business analysis.

So why not support yourself with a proven outsourcing provider who has experience in similar assignments? After all, despite the best planning, unforeseen obstacles may appear during the implementation. This is when the support of a software house, which is well acquainted with similar cases, will prove particularly helpful. 

At Nextrope we have worked on a wide variety of DeFi applications and are very familiar with the specifications of such projects and the various problems that arise during their implementation. If you want a solution that will surprise the market, contact our team.

Tagi

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!