Account Abstraction Ecosystem Growth – Data & Statistics

Karolina

07 Dec 2023
Account Abstraction Ecosystem Growth – Data & Statistics

As of December 2023, a sequence of indicators highlights the escalating attention garnered by Account Abstraction impactful concept. The cumulative count of active accounts has reached 1,500,000 and the aggregate count of successfully executed UserOperations has reached 7,230,000 (Data: DUNE)

Account Abstraction

What is Account Abstraction?

Account Abstraction (AA) has emerged as a pivotal innovation in the realm of blockchain and cryptocurrencies, redefining user interactions and broadening the scope of decentralized applications. As we delve into 2023, AA's ecosystem has witnessed a remarkable upsurge, underscoring its growing significance in the industry. This article aims to dissect this surge, unraveling the intricate web of data and statistics that underscore the expansion of AA. By exploring the latest trends, technological advancements, and the economic implications within this dynamic domain, we seek to provide a detailed perspective on the growth trajectory of Account Abstraction and its profound impact on the future of Web3 and digital finance.

The Surge of Account Abstractions in 2023

In 2023, the Account Abstraction (AA) sector has experienced a remarkable upswing, marked by the deployment of over 1,500,000 ERC-4337 accounts across key platforms like Ethereum, Arbitrum, Optimism, and Polygon. This notable increase reflects a growing user base and heightened activity in the AA ecosystem. Enhanced user operations have become evident, showcasing a broader acceptance and integration of AA into the mainstream blockchain infrastructure. This surge not only signifies technological progress but also indicates a shift in how users interact with blockchain applications, paving the way for more intuitive and accessible decentralized services.

Platform-Specific Growth Analysis

Polygon Account Abstraction Statistics

Polygon's Leap Forward: Polygon has made notable strides in AA, driven by its user-friendly approach and strategic collaborations. The platform has seen a surge in account numbers and user operations, contributing significantly to the AA ecosystem.

DATA as of 7th December:

1,081,723 - Total Accounts

5,846,241 - Total Successful UserOps (Pseudo-transactions made by smart accounts)

3,992,105 - Total ERC-4337 Bundle Transactions (Bundles of UserOps executed together)

156,363.46 MATIC - Polygon Total Gas Sponsored by Paymasters (Gas fees paid on behalf of users by paymasters)

Source: DUNE

Optimism Account Abstraction Statistics

This platform has demonstrated substantial growth in AA. It focus on scaling solutions and user experience improvements has led to increased account growth and user operations, indicating their growing influence in the AA landscape.

DATA as of 7th December:

192,722 - Total Accounts

576,854 - Total Successful UserOps (Pseudo-transactions made by smart accounts)

464,609 - Total ERC-4337 Bundle Transactions (Bundles of UserOps executed together)

159.52 ETH - Optimism Total Gas Sponsored by Paymasters (Gas fees paid on behalf of users by paymasters)

Source: DUNE

Arbitrum Account Abstraction Statistics

Arbitrum has seen a significant uptick in AA adoption. Its focus on scalability and efficient transaction processing has attracted a growing number of users and developers, leading to an increase in the deployment of AA accounts and the volume of user operations.

DATA as of 7th December:

234,278 - Total Accounts

358,976 - Total Successful UserOps (Pseudo-transactions made by smart accounts)

334,007 - Total ERC-4337 Bundle Transactions (Bundles of UserOps executed together)

115.19 ETH - Arbitrum Total Gas Sponsored by Paymasters (Gas fees paid on behalf of users by paymasters)

Source: DUNE

The Role of Paymasters and Bundlers

In the AA ecosystem, Paymasters and Bundlers play a critical role. Paymasters act as financial guarantors, ensuring transaction fees are covered, while Bundlers aggregate transactions for efficiency and speed. 2023 has seen a significant growth in transactions involving both, reflecting their increasing importance in the ecosystem. This growth not only enhances the user experience by simplifying transactions but also contributes to the robustness and scalability of the AA framework.

Financial Implications

Financially, the growth in AA has had notable implications. The increase in transactions has led to higher revenue for both Bundlers and Paymasters. This growth impacts gas fees, influencing the overall economic dynamics within the blockchain ecosystem. The expansion of AA thus plays a vital role in shaping the financial landscape of decentralized networks.

Conclusion

The growth of Account Abstraction in 2023 marks a significant milestone in the blockchain sector. The increasing role of Paymasters and Bundlers, coupled with the financial implications of this growth, underscores the evolving nature of blockchain technology. This expansion not only enhances user experience and transaction efficiency but also has a profound economic impact, paving the way for further innovations and adoption in the broader blockchain ecosystem.

READ about successful case studies

If you are interested in utilizing Account Abstraction or other blockchain-based solutions for your project, please reach out to contact@nextrope.com

FAQ

What is the growth trend of Account Abstraction in 2023?

  • Over 1.5 million ERC-4337 accounts deployed, reflecting increased activity.

What are the specific growth statistics for Polygon, Optimism, and Arbitrum in terms of Account Abstraction?

  • All platforms show substantial growth in accounts and successful operations.

The financial implications of the growth in Account Abstraction

  • Increased revenue for Bundlers and Paymasters, impacting gas fees and the overall economy.

What roles do Paymasters and Bundlers play in the Account Abstraction ecosystem?

  • Paymasters ensure fee coverage, while Bundlers aggregate transactions for efficiency.

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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