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.
The Future of AI in Real Estate: Trends and Forecasts for 2026–2030
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
Increased accuracy in forecasts and valuations, minimizing business risks
Enhanced customer experience and shorter transaction times.
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
The Ultimate Web3 Backend Guide: Supercharge dApps with APIs
Tomasz Dybowski
04 Mar 2025
Introduction
Web3 backend development is essential for building scalable, efficient and decentralized applications (dApps) on EVM-compatible blockchains like Ethereum, Polygon, and Base. A robust Web3 backend enables off-chain computations, efficient data management and better security, ensuring seamless interaction between smart contracts, databases and frontend applications.
Unlike traditional Web2 applications that rely entirely on centralized servers, Web3 applications aim to minimize reliance on centralized entities. However, full decentralization isn't always possible or practical, especially when it comes to high-performance requirements, user authentication or storing large datasets. A well-structured backend in Web3 ensures that these limitations are addressed, allowing for a seamless user experience while maintaining decentralization where it matters most.
Furthermore, dApps require efficient backend solutions to handle real-time data processing, reduce latency, and provide smooth user interactions. Without a well-integrated backend, users may experience delays in transactions, inconsistencies in data retrieval, and inefficiencies in accessing decentralized services. Consequently, Web3 backend development is a crucial component in ensuring a balance between decentralization, security, and functionality.
This article explores:
When and why Web3 dApps need a backend
Why not all applications should be fully on-chain
Architecture examples of hybrid dApps
A comparison between APIs and blockchain-based logic
This post kicks off a Web3 backend development series, where we focus on the technical aspects of implementing Web3 backend solutions for decentralized applications.
Why Do Some Web3 Projects Need a Backend?
Web3 applications seek to achieve decentralization, but real-world constraints often necessitate hybrid architectures that include both on-chain and off-chain components. While decentralized smart contracts provide trustless execution, they come with significant limitations, such as high gas fees, slow transaction finality, and the inability to store large amounts of data. A backend helps address these challenges by handling logic and data management more efficiently while still ensuring that core transactions remain secure and verifiable on-chain.
Moreover, Web3 applications must consider user experience. Fully decentralized applications often struggle with slow transaction speeds, which can negatively impact usability. A hybrid backend allows for pre-processing operations off-chain while committing final results to the blockchain. This ensures that users experience fast and responsive interactions without compromising security and transparency.
While decentralization is a core principle of blockchain technology, many dApps still rely on a Web2-style backend for practical reasons:
1. Performance & Scalabilityin Web3 Backend Development
Smart contracts are expensive to execute and require gas fees for every interaction.
Offloading non-essential computations to a backend reduces costs and improves performance.
Caching and load balancing mechanisms in traditional backends ensure smooth dApp performance and improve response times for dApp users.
Event-driven architectures using tools like Redis or Kafka can help manage asynchronous data processing efficiently.
2. Web3 APIs for Data Storage and Off-Chain Access
Storing large amounts of data on-chain is impractical due to high costs.
APIs allow dApps to store & fetch off-chain data (e.g. user profiles, transaction history).
Decentralized storage solutions like IPFS, Arweave and Filecoin can be used for storing immutable data (e.g. NFT metadata), but a Web2 backend helps with indexing and querying structured data efficiently.
3. Advanced Logic & Data Aggregation in Web3 Backend
Some dApps need complex business logic that is inefficient or impossible to implement in a smart contract.
Backend APIs allow for data aggregation from multiple sources, including oracles (e.g. Chainlink) and off-chain databases.
Middleware solutions like The Graph help in indexing blockchain data efficiently, reducing the need for on-chain computation.
4. User Authentication & Role Management in Web3 dApps
Many applications require user logins, permissions or KYC compliance.
Blockchain does not natively support session-based authentication, requiring a backend for handling this logic.
Tools like Firebase Auth, Auth0 or Web3Auth can be used to integrate seamless authentication for Web3 applications.
5. Cost Optimization with Web3 APIs
Every change in a smart contract requires a new audit, costing tens of thousands of dollars.
By handling logic off-chain where possible, projects can minimize expensive redeployments.
Using layer 2 solutions like Optimism, Arbitrum and zkSync can significantly reduce gas costs.
Web3 Backend Development: Tools and Technologies
A modern Web3 backend integrates multiple tools to handle smart contract interactions, data storage, and security. Understanding these tools is crucial to developing a scalable and efficient backend for dApps. Without the right stack, developers may face inefficiencies, security risks, and scaling challenges that limit the adoption of their Web3 applications.
Unlike traditional backend development, Web3 requires additional considerations, such as decentralized authentication, smart contract integration, and secure data management across both on-chain and off-chain environments.
Here’s an overview of the essential Web3 backend tech stack:
1. API Development for Web3 Backend Services
Node.js is the go-to backend runtime good for Web3 applications due to its asynchronous event-driven architecture.
NestJS is a framework built on top of Node.js, providing modular architecture and TypeScript support for structured backend development.
2. Smart Contract Interaction Libraries for Web3 Backend
Ethers.js and Web3.js are TypeScript/JavaScript libraries used for interacting with Ethereum-compatible blockchains.
3. Database Solutions for Web3 Backend
PostgreSQL: Structured database used for storing off-chain transactional data.
MongoDB: NoSQL database for flexible schema data storage.
Firebase: A set of tools used, among other things, for user authentication.
The Graph: Decentralized indexing protocol used to query blockchain data efficiently.
Infura, Alchemy, QuickNode: Blockchain RPC node providers offering API access to Ethereum, Polygon and other networks.
When It Doesn't Make Sense to Go Fully On-Chain
Decentralization is valuable, but it comes at a cost. Fully on-chain applications suffer from performance limitations, high costs and slow execution speeds. For many use cases, a hybrid Web3 architecture that utilizes a mix of blockchain-based and off-chain components provides a more scalable and cost-effective solution.
In some cases, forcing full decentralization is unnecessary and inefficient. A hybrid Web3 architecture balances decentralization and practicality by allowing non-essential logic and data storage to be handled off-chain while maintaining trustless and verifiable interactions on-chain.
The key challenge when designing a hybrid Web3 backend is ensuring that off-chain computations remain auditable and transparent. This can be achieved through cryptographic proofs, hash commitments and off-chain data attestations that anchor trust into the blockchain while improving efficiency.
For example, Optimistic Rollups and ZK-Rollups allow computations to happen off-chain while only submitting finalized data to Ethereum, reducing fees and increasing throughput. Similarly, state channels enable fast, low-cost transactions that only require occasional settlement on-chain.
A well-balanced Web3 backend architecture ensures that critical dApp functionalities remain decentralized while offloading resource-intensive tasks to off-chain systems. This makes applications cheaper, faster and more user-friendly while still adhering to blockchain's principles of transparency and security.
Example: NFT-based Game with Off-Chain Logic
Imagine a Web3 game where users buy, trade and battle NFT-based characters. While asset ownership should be on-chain, other elements like:
Game logic (e.g., matchmaking, leaderboard calculations)
User profiles & stats
Off-chain notifications
can be handled off-chain to improve speed and cost-effectiveness.
Architecture Diagram
Below is an example diagram showing how a hybrid Web3 application splits responsibilities between backend and blockchain components.
Comparing Web3 Backend APIs vs. Blockchain-Based Logic
Feature
Web3 Backend (API)
Blockchain (Smart Contracts)
Change Management
Can be updated easily
Every change requires a new contract deployment
Cost
Traditional hosting fees
High gas fees + costly audits
Data Storage
Can store large datasets
Limited and expensive storage
Security
Secure but relies on centralized infrastructure
Fully decentralized & trustless
Performance
Fast response times
Limited by blockchain throughput
Reducing Web3 Costs with AI Smart Contract Audit
One of the biggest pain points in Web3 development is the cost of smart contract audits. Each change to the contract code requires a new audit, often costing tens of thousands of dollars.
Speeds up development cycles by catching vulnerabilities early.
Improves security by providing quick feedback.
This AI-powered solution will be a game-changer for the industry, making smart contract development more cost-effective and accessible.
Conclusion
Web3 backend development plays a crucial role in scalable and efficient dApps. While full decentralization is ideal in some cases, many projects benefit from a hybrid architecture, where off-chain components optimize performance, reduce costs and improve user experience.
In future posts in this Web3 backend series, we’ll explore specific implementation details, including:
Next Enterprises Sp. z o.o. is implementing a project co-financed by the European Funds, titled "Smart Contract Auditing with Artificial Intelligence". The goal of the project is to develop and deploy an advanced AI model that enables efficient analysis, vulnerability detection, and security auditing of smart contracts, taking into account their complexity and uniqueness.
Planned Project Tasks:
Development of an AI model trained on Solidity keywords;
Creation of an effective model in simulated conditions;
Analysis of the unpredictability of compiled code execution within the Ethereum Virtual Machine (EVM) in the context of the developed model in a controlled environment;
Validation of the model in real-world conditions.
Target Groups:
Specialized audit firms focused on smart contract security;
Companies developing and/or deploying smart contracts on various platforms;
Exchanges, wallet providers, and decentralized applications (dApps) in the blockchain sector;
Government agencies or industry compliance bodies responsible for blockchain technology regulation;
Smart contract security specialists and developers.
The implementation of the developed tool will enable automated and efficient auditing of smart contracts. The model will provide detailed insights and recommendations for optimizing transaction costs and improving contract performance. As a result, users will be able to make informed decisions, enhancing security and operational efficiency within the blockchain ecosystem. Key benefits stem from the model’s training on smart contract code, audit data, and detected vulnerabilities. Additionally, the incorporation of chaos theory principles will allow for more precise risk and anomaly forecasting.
By deploying this advanced AI model, the project will enhance the security, efficiency, and accessibility of blockchain technology for end users. This will translate into tangible social and economic benefits, including:
Economic Security
Business and Financial Security
Increased Public Trust
Optimization of Transaction Costs
Support for Innovation and Entrepreneurship
Education and Public Awareness
Project Value: 4,173,953.24 PLN European Funds Contribution: 3,090,156.39 PLN
#EUFunds #EuropeanFunds
Challenges in Smart Contract Auditing
Smart contracts have become a fundamental component of blockchain technology, eliminating intermediaries, and automating processes. However, their growing significance also introduces new challenges, particularly in ensuring security and compliance with industry standards.
Traditional smart contract audits rely heavily on manual code reviews, which are expensive, time-consuming, and prone to human error. As cyber threats continue to evolve, the use of advanced technologies to support the auditing process is imperative.
The Role of AI in Data Analysis
Artificial intelligence (AI) introduces a new paradigm in smart contract security assessment by leveraging its capability to process vast amounts of data and identify patterns that may go unnoticed with traditional auditing methods. AI enables:
Automated code analysis and real-time detection of potential vulnerabilities,
Optimization of auditing processes by reducing human errors and improving threat identification efficiency,
Better adaptation to evolving regulatory requirements and emerging threats within the blockchain ecosystem,
Rapid analysis of large datasets, allowing for quick insights and the detection of non-obvious dependencies in smart contract code.
By utilizing AI, the auditing process becomes more comprehensive, precise, and scalable, enabling continuous risk monitoring and adaptation to new attack vectors.
A New Era of Smart Contract Security with AI
With the support of European Funds under the European Funds for a Modern Economy (FENG) program, we are conducting research on next-generation blockchain auditing methods, reinforcing Nextrope’s position as a leader in innovative technology solutions.
The "Smart Contract Auditing with Artificial Intelligence (AI)" project contributes to key aspects of blockchain security by:
Automating smart contract audits, accelerating verification processes, and improving their accuracy,
Optimizing costs, making professional audits more accessible to a broader range of entities,
Raising security standards and enhancing regulatory compliance,
Increasing trust in smart contracts, fostering broader technology adoption.
Interested in learning more about our project or discovering how to utilize AI in your company? 📩 Contact us at contact@nextrope.com for further details!
We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking “Accept”, you consent to the use of ALL the cookies.
This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may affect your browsing experience.
Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.
Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.