Avalanche’s Investment in Real-World Assets Tokenization

Karolina

07 Sep 2023
Avalanche’s Investment in Real-World Assets Tokenization

As a link between the digital and physical realms, tokenization transforms real-world assets into blockchain versions, paving the way for tangible and intangible assets to coexist harmoniously on a single platform. The Avalanche Foundation is at the vanguard of this innovation, recognizing the potential in asset tokenization and trailblazing its widespread adoption.

The Avalanche Vista Initiative - Tokenization

Through its astonishing $50M allocation, the Avalanche Foundation has demonstrated its deep dedication to advancing asset tokenization. Called "Avalanche Vista," this program transcends mere financial commitment by embodying a mission-driven quest to reveal the unmatched potential of tokenization. By crafting on-chain digital representations of various assets, Avalanche aspires to inject higher speed, scalability, and adaptability into asset tokenization. The ultimate aim is indisputable: facilitating a financial system that emphasizes accessibility but also excels in efficiency and cost-effectiveness. This vision relies upon Avalanche's innovative consensus mechanism, its distinct Subnet architecture, and relentless pursuit of technical innovation.

Scope of the Initiative

Avalanche Vista encompasses a broad range of asset types without limitation. Assets spanning the liquidity spectrum—whether equity, credit, real estate, or commodities—will be taken into account. The initiative even pertains to blockchain-native assets, highlighting its all-encompassing strategy. Notable milestones in the journey of asset tokenization support the inception of this initiative. Securitize's trailblazing action to tokenize an interest in a flagship KKR fund on the Avalanche blockchain marks an unprecedented digital venture in the U.S. Moreover, the launch of IntainMARKETS (an administration platform exclusively designed for asset-backed securities) and the Avalanche Spruce testnet both signify Avalanche's unwavering commitment to exploring and expanding the benefits of OnFi.

Asset Tokenization's Value Proposition

Capital Markets and Blockchain Advantages

Asset tokenization is a groundbreaking innovation in capital markets, driven by continuous technological progress that reshapes industries. The melding of blockchain technology with asset tokenization has the potential to completely transform traditional financial operations. As stated by John Wu, President of Ava Labs, asset tokenization is more than just a futuristic notion; it is an active force changing the current financial landscape. The impressive momentum of institutions embracing on-chain practices highlights the importance of this movement, as demonstrated by the ambitious initiative from the Avalanche Foundation.

The core element in this transformation is incorporating blockchain's capabilities. By merging blockchain with asset tokenization, enduring challenges such as inefficiency, restricted accessibility, and elevated operational costs, which have historically burdened traditional financial systems, can be addressed. Real-world assets are represented as digital tokens on the blockchain, establishing an optimized ecosystem. This ecosystem not only automates intricate processes like asset issuance, settlement, transfer, and administration but also guarantees transparency, security, and efficiency.

Expanding Access to Private Market Investing

Restricted access to private market investing has been a persistent obstacle in the financial sector. Previously, this domain was exclusive to large institutional investors and ultra-high-net-worth individuals due to hindrances like significant operational costs and limited liquidity. Such barriers carry considerable consequences as they exclude smaller investors from lucrative opportunities for wealth generation.

Asset tokenization serves as a revolutionary solution in this context. Joining on-chain asset issuance and administration with tokenization forms powerful tools that aim to provide equitable access to private markets. Through developing digital representations of assets on the blockchain, fractional ownership becomes achievable. Smaller investors are now able to engage in formerly unattainable markets with reduced entry barriers, leading not only to increased inclusivity but also improved overall market liquidity.

The possible reverberations of this democratization are immense and could transform the investment landscape, empowering a more extensive array of individuals to actively contribute to wealth creation. It is no surprise that industry specialists predict traditional securities will experience a digital metamorphosis within the coming decade, with the tokenized securities market predicted to achieve astonishing numbers by 2030.

Progress in On-Chain Financial Services and Asset Tokenization

Traditional Finance and Crypto On-Chain Applications

The financial landscape is rapidly transforming, with the implementation of on-chain solutions advancing at an unexpected pace. Conventional financial institutions have acknowledged the revolutionary impact of pairing on-chain functions with off-chain assets.

In just the last year, there has been a remarkable increase in the growth and incorporation of on-chain applications. It demonstrates the extensive range and adaptability of this technology. Tokenization, in particular, has supported the effortless transition of typically off-chain assets to on-chain environments. More than a simple technological change, this shift signifies a new era of heightened efficiency, clarity, and accessibility.

A prime example is IntainMARKETS, a management platform explicitly crafted for asset-backed securities. Its birth within the Avalanche Evergreen Subnet emphasizes the push for creating structured on-chain solutions that address complex fiscal needs.

Intain's Founder and CEO, Siddhartha, perfectly captured the spirit driving these innovations. He articulated that transitioning sections of asset administration onto blockchain enables a harmonized workflow and a unified system of record. Ultimately, both service providers and investors can expect an enhanced user experience.

Conclusion

The exciting juncture at which on-chain finance and asset tokenization find themselves is set to revolutionize the financial landscape. The integration of traditional systems with groundbreaking blockchain technology marks the beginning of a more inclusive, efficient, and transparent financial future. With institutions like the Avalanche Foundation at the forefront, we're seeing today's promises materialize into tomorrow's realities. Navigating through this transformative period, it becomes evident that the fusion of blockchain and finance goes beyond just being the future. It is the present and is here to persist.

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Master UI Component Creation with AI: The Ultimate Guide for Developers

Gracjan Prusik

24 Mar 2025
Master UI Component Creation with AI: The Ultimate Guide for Developers

Introduction

Modern frontend development is evolving rapidly, and creating UI components with AI tools is helping developers save time while enhancing interface quality. With AI, we can not only speed up the creation of UI components but also improve their quality, optimize styles, and ensure better accessibility.

This article explores how creating UI components with AI is transforming frontend development by saving time and improving workflows. Specifically, we will discuss:

  • Generating components from images,
  • AI for style analysis and optimization,
  • Automatic style conversion and code migration,
  • AI in generating UI animations.

Creating UI Components with AI from Images

One of the interesting applications of AI in frontend development is the ability to generate components from an image. AI can recognize the structure of the interface and generate HTML/CSS or JSX code that matches the provided image. One of the most popular tools for UI creation is Lovable.

For testing, let's see how the tool performs in creating a simple contact form from the page you are currently on, which is Nextrope.

Query:

"Recreate the image I've sent you in Next.js using CSS."

Sample image used in the query:

The result received:

Tworzenie komponentów UI - Wygenerowany widok

Lovable did an excellent job transforming the image into code. The view is fully responsive. It’s important to remember that the more precise the request, the better the AI will replicate the expected view. However, even with a simple command, the tool performed surprisingly well.

Of course, AI has its limitations. It still makes quite a few mistakes. The generated code still requires review and fixes from the developer, but in some cases, the entire process is significantly sped up—correcting the code often takes less time than creating the component from scratch.

Optimizing UI Components with AI Tools for Style Improvements

This problem of inaccurate code reproduction by AI can be partially addressed by using it to analyze and improve styles. Tools like ChatGPT, DeepSeek and Claude are capable of not only generating code but also diagnosing CSS errors and suggesting why a particular style might not be working as expected.

Simple example: Why is the div not centered?

Query: "Why is this div not centered?"

AI analyzes the code and provides the following response:

Problem: The parent container does not have a defined width or display: flex.
Solution: Add the appropriate styles to the parent container.

.parent {
  display: flex;
  justify-content: center;
  align-items: center;
  width: 100vw;
  height: 100vh;
}

AI for Automatic Style Conversion and Code Migration in UI Components

AI can assist with style conversion between different technologies, such as transferring code from traditional CSS to Styled Components or Tailwind CSS.

Let's assume we have a style written in traditional CSS:

.button {
  background-color: blue;
  color: white;
  padding: 10px 20px;
  border-radius: 5px;
  transition: background-color 0.3s ease;
}

.button:hover {
  background-color: darkblue;
}

We can use AI for automatic conversion to Styled Components:

import styled from "styled-components";

const Button = styled.button`
  background-color: blue;
  color: white;
  padding: 10px 20px;
  border-radius: 5px;
  transition: background-color 0.3s ease;

  &:hover {
    background-color: darkblue;
  }
`;

export default Button;

AI can also assist in migrating code between frameworks, such as from React to Vue or from CSS to Tailwind.

This makes style migration easier and faster.

How AI Enhances UI Animation Creation

Animations are crucial for enhancing user experience in interfaces, but they are not always provided in the project specification. In such cases, developers have to come up with how the animations should look, which can be time-consuming and require significant creativity. AI, in this context, becomes helpful because it can automatically generate CSS animations or animations using libraries like Framer Motion, saving both time and effort.

Example: Automatically Generated Button Animation

Suppose we need to add a subtle scaling animation to a button but don't have a ready-made animation design. Instead of creating it from scratch, AI can generate the code that meets our needs.

Code generated by AI:

import { motion } from "framer-motion";

const AnimatedButton = () => (
  <motion.button
    whileHover={{ scale: 1.1 }}
    whileTap={{ scale: 0.9 }}
    className="bg-blue-500 text-white px-4 py-2 rounded-lg"
  >
    Press me
  </motion.button>
);

In this way, AI accelerates the animation creation process, providing developers with a simple and quick option to achieve the desired effect without the need to manually design animations from scratch.

Summary

AI significantly accelerates the creation of UI components. We can generate ready-made components from images, optimize styles, transform code between technologies, and create animations in just a few seconds. Tools like ChatGPT, DeepSeek, Claude and Lovable are a huge help for frontend developers, enabling faster and more efficient work.

In the next part of the series, we will take a look at:

If you want to learn more about how AI is impacting the entire automation of frontend processes and changing the role of developers, check out our blog article: AI in Frontend Automation – How It's Changing the Developer's Job?

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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