The Future of Decentralized Finance: Interoperability and Cross-Chain Solutions

Karolina

26 May 2023
The Future of Decentralized Finance: Interoperability and Cross-Chain Solutions

The financial landscape has been revolutionized by decentralized finance (DeFi), which utilizes blockchain technology, artificial intelligence (AI), and cryptocurrencies to develop innovative and transparent financial solutions. One crucial element driving the future of DeFi is interoperability and cross-chain solutions, as the space experiences rapid growth. This article will discuss the importance of interoperability within the DeFi ecosystem and examine cross-chain solutions, concentrating on their impact on the future of decentralized finance.

Understanding Interoperability in DeFi

Often known as DeFi, decentralized finance signifies a fundamental shift in our understanding and engagement with conventional financial systems. DeFi, built upon blockchain technology, seeks to democratize finance by removing intermediaries, facilitating peer-to-peer transactions, and granting open and transparent financial services to anyone with internet access. The DeFi ecosystem has experienced tremendous growth in recent years, encompassing lending and borrowing platforms, decentralized exchanges, and yield farming, consequently attracting billions of dollars in investments and garnering interest from both institutional and retail investors.

Nonetheless, as the DeFi landscape grows more expansive and numerous blockchain networks are established, the demand for interoperability becomes increasingly vital. Interoperability denotes the capacity for various blockchain networks and decentralized applications (dApps) to communicate and seamlessly interact with each other. This interconnectedness is essential for DeFi's future because it enables efficient asset, data, and value transfers across diverse blockchain networks, opening up a realm of possibilities and promoting collaboration among distinct projects.

Check out our article about the future of DeFi

The Promise of Cross-Chain Solutions

Cross-Chain Solutions are rapidly emerging as the linchpin of future decentralized finance, promising to overcome one of the most significant barriers in the space - the lack of interoperability. At its core, a Cross-Chain Solution allows different blockchain platforms to communicate and interact with each other, enabling the seamless exchange of information and assets. This is a game-changer for DeFi as it could potentially unlock massive liquidity pools trapped within isolated blockchain ecosystems.

In addition, Cross-Chain Solutions also bring the potential for enhanced scalability, security, and efficiency. They provide the means for DeFi applications to leverage the strengths of multiple blockchain networks, bypassing the constraints tied to a single blockchain. This could lead to the creation of more robust and versatile DeFi services, opening up a myriad of opportunities for both developers and users.

Furthermore, Cross-Chain Solutions can foster a more inclusive and interconnected DeFi landscape. By allowing different blockchain networks to interoperate, they eliminate the barriers between disparate communities, bringing together diverse participants under a unified financial ecosystem. In essence, Cross-Chain Solutions hold the promise of creating a truly global and decentralized financial system, thus taking us one step closer to the original vision of blockchain technology.

Use Cases of Cross-Chain Solutions in DeFi

Use cases of Cross-Chain Solutions

Cross-chain solutions are already playing a crucial role in the DeFi space by enabling the creation of innovative financial products and services that were previously impossible. Here are some real-world use cases of how cross-chain technology is being used in DeFi today:

  • Cross-Chain Swaps: Cross-chain swaps allow users to trade assets between different blockchain networks without the need for a centralized exchange or intermediary. These swaps use atomic swaps to ensure the transaction is trustless and secure.
  • Liquidity Pools: Cross-chain liquidity pools enable users to provide liquidity across different blockchain networks. This means that users can earn fees and rewards for their participation. Liquidity pools use wrapped assets to represent the underlying assets, making it possible for users to provide liquidity across different blockchain networks.
  • Cross-Chain Derivatives: Cross-chain derivatives make it possible for users to create complex financial instruments that span multiple blockchain networks. For example, users can create synthetic assets that represent a basket of assets from different blockchain networks, or they can create options contracts that are settled on a different blockchain network.
  • Interoperability: Cross-chain technology facilitates interoperability between different DeFi protocols and platforms. This makes it possible to create new financial products and services that leverage the strengths of different platforms. For instance, users can use cross-chain technology to move assets between decentralized exchanges (DEXs) and lending protocols, or to create new lending products that span multiple blockchain networks​. 

Challenges and Considerations

The immense potential of cross-chain solutions in DeFi comes with several challenges and considerations that need attention. One significant obstacle is regulatory concerns and compliance requirements, given that multiple jurisdictions and regulatory frameworks are involved in cross-chain transactions. It is a complicated task to ensure compliance with these varied regulations while preserving DeFi's decentralized essence, necessitating inventive solutions and cooperation with regulatory authorities.

Moreover, addressing security and trust issues is crucial since the effortless transfer of assets and data across various chains creates new attack vectors and vulnerabilities. To safeguard user funds and uphold trust within the DeFi ecosystem, stringent security measures such as advanced cryptographic methods and smart contract audits are imperative.

Furthermore, attaining standardization and governance for cross-chain interoperability is vital to guarantee compatibility and smooth communication between different blockchain networks. The establishment of shared protocols, norms, and governance structures will encourage interoperability and promote the extensive adoption of cross-chain solutions in DeFi.

Finally, tackling user experience and adoption challenges is essential for achieving mainstream acceptance. Simplification of user interfaces, improved accessibility, and user education about the merits and functionalities of cross-chain solutions are all crucial elements for expanding the user base and realizing the full potential of DeFi interoperability.

The future with Cross-Chain Solutions

One of the key trends to watch out for is the rise of multi-chain DeFi platforms. With the advent of cross-chain technology, we are likely to see an explosion of platforms that operate seamlessly across multiple blockchain networks. This will open up new opportunities for users, allowing them to take advantage of the unique strengths and features of different blockchains. For example, users might be able to earn higher yields on one platform, enjoy lower transaction fees on another, and access unique financial products on a third, all without leaving the comfort of a single, unified platform.

Additionally, Cross-Chain Solutions will likely drive the development of more advanced and complex financial instruments. As demonstrated by the rise of cross-chain derivatives, there is significant potential for the creation of innovative financial products that leverage the interoperability of different blockchains. This could usher in a new era of financial sophistication and accessibility, in line with the ethos of DeFi.

Finally, Cross-Chain Solutions could play a key role in the mass adoption of DeFi. By breaking down the barriers between different blockchain networks, they could help bring about a truly global and inclusive financial system. Users from all corners of the world, irrespective of their local financial infrastructure, might be able to access a plethora of financial services, from basic savings and lending to advanced trading and investment opportunities.

In essence, the future of DeFi with Cross-Chain Solutions looks promising. The combination of interoperability, efficiency, and inclusivity brought about by this technology has the potential to redefine the financial landscape, making it more democratic, accessible, and resilient. The vision of a truly decentralized financial system might not be too far off.

Conclusion

Cross-chain solutions are revolutionizing the future of decentralized finance (DeFi). Interoperability, facilitated by cross-chain technology, is becoming increasingly crucial as the DeFi ecosystem expands. It enables seamless communication and interaction between blockchain networks and decentralized applications (dApps), opening up new possibilities and promoting collaboration. Cross-chain solutions offer significant advantages, including unlocking liquidity, enhancing scalability and security, and fostering inclusivity. They enable cross-chain swaps, liquidity pools, and derivatives, while facilitating interoperability between DeFi protocols and platforms. However, challenges such as regulatory compliance, security, standardization, and user experience must be addressed. The future with cross-chain solutions holds the promise of multi-chain DeFi platforms, advanced financial instruments, and mass adoption, ultimately reshaping the financial landscape into a more democratic, accessible, and resilient system.

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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!