Insourcing blockchain vs outsourcing blockchain

Maciej Zieliński

28 Apr 2021
Insourcing blockchain vs outsourcing blockchain

Despite dynamic development of the blockchain industry, one thing has not changed: the success of the project is closely related to the knowledge and experience of the programmers working on it. Therefore, it is crucial to answer the question which is the better choice: blockchain outsourcing or insourcing blockchain?

Various enterprises, from small startups to biggest banks and shipping companies all over the world, show their interest in the blockchain technology. That’s why there is no universal answer. Before making the decision, most importantly you should thoroughly evaluate your company’s needs, and the characteristics of the blockchain project you want to implement. To make it easier for you, we at Nextrope analyzed pros and cons of both solutions, 

Insourcing Blockchain

It’s worth noting that finding a Blockchain programmer is not an easy task. According to statistics, on average there are 14 job offers for each specialist.  Most likely the situation won’t change for better, as U.S. Bureau of Labor Statisticresearch shows, demand for Blockchain programmers will continue to grow. 

On the other hand, if you succeed to hire a Blockchain programmer, insourcing Blockchain can give you more control over the project and increase work effectiveness. 

Insourcing Blockchain - Pros:

  • potentially more control
  • project’s technological independence 
  • direct and immediate instruction flow

Insourcing Blockchain - Cons:

  • large costs of maintaining internal team
  • possible failure of recruitment process
  • versatility of employed specialists decreasing with time
  • time consuming recruitment process 

Internal teams are often good at general programming tasks but when it comes to the newest technologies like Blockchain, many companies eventually discover that their staff is not properly qualified to develop these technologies. Moreover the recruitment process and onboarding for new employees might turn out rather costly and time consuming. 

insourcing blockchain

Hiring your own team might be beneficial when:

  • You want to diversify an existing team by hiring new employees who may bring new, fresh ideas. 
  • You need a Blockchain programmer for a longer run, not only for a short period.
  • You are able to pay for programmers workplace, necessary equipment, hiring taxes and insurances. 
  • You have the necessary time to introduce the project to the new hire.

Hiring an insource programmer is most often beneficial for large companies that have short and long-term goals related with software development. To make hiring the programmer worthwhile, the team should be able to specify the scope of knowledge and skills that they search need. Only then, the company can effectively look for a suitable employee. 

Outsourcing Blockchain vs insourcing Blockchain

Outsourcing Blockchain most often takes two forms: independent blockchain programmer or a whole software house. The first option is most suitable for short-term projects that require task-oriented results. On the other hand, a software house can definitely satisfy more outsourcing blockchain related needs: from a single developer for a specific task to an interdisciplinary team of blockchain experts that besides programming can also take care of creating business logic or provide legal advice. 

Modern software houses provide not only programming but also consulting services, the experience of it’s specialists can give you a new, fresh look at your project and allow you to adjust it to technological reality. 

Outsourcing Blockchain - Pros:

  • lower project realization costs 
  • vast list of various available technologies and tools 
  • accelerating the product launch 
  • access to comprehensive knowledge of blockchain experts, including but not limited to programmers
  • no need for recruitment process 
  • possibility to fully focus on the remaining elements of the project
  • if needed - faster project scaling
  • predominantly high product quality (depending on chosen company)

Outsourcing Blockchain - Cons:

  • technological expertise comes from outside the company
  • no direct control over the project (however, a good software house allows you to contact not only the project manager but also any employee responsible for your order) 
insourcing blockchain

Outsourcing Blockchain is most beneficial when:

  • You know specifically what you need from the team and you can communicate these needs (in the case of a team or a freelancer that connects closely with your team)
  • You don’t have enough knowledge about the technical specification but you know exactly what effect you want to achieve 
  • You created a specification and tasks list but have limited time to hire and train new employees
  • You want to minimize costs - outsourcing is most likely less costly than maintaining an internal team 

Outsourcing Blockchain vs insourcing blockchain - Nextrope

Nextrope is a polish software house providing outsourcing Blockchain services. Each project we approach with extraordinary attention to details and personal involvement. Among our clients we have revolutionary financial and legal startups, and one of the biggest banks in Poland - Alior Bank. More stories of our success here

With years of experience, we simply know what makes projects fantastic. If you want to know why Nextrope - contact us for free consulting: contact@nextrope.com

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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