At Revelis we work daily with AI and Big Data Analytics technologies and we observe this transformation from the inside. In this article we explain what vibe coding tools are, why they are changing the rules of software development and which platforms are most effective in 2026. To explore the conceptual foundations, you can start from our article “Vibe Coding AI”.

What vibe coding tools are and why they are reshaping software development

Vibe coding tools are not just an evolution of traditional code editors: they represent a new software development paradigm in which the programmer no longer writes instructions sequentially, but interacts with an AI agent to translate ideas into working applications. The developer becomes a sort of orchestra conductor: they define the vision, architecture and user experience, while artificial intelligence handles technical implementation and repetitive tasks, from boilerplate to syntactic debugging.

This approach redefines iteration speed. Where in the past creating a working prototype required days of environment setup, dependency management and service code, today vibe coding tools take you from idea to deployment in minutes. The real game-changer is the ability to maintain context: AI doesn’t just suggest the next line; it understands the entire codebase and proposes structural changes consistent with the project’s style and architecture.

The outcome is a dual leverage: on one hand, access to software creation is democratised, opening the door to designers, founders and product roles with less vertical technical skills; on the other, professionals gain an unprecedented cognitive amplifier that multiplies productivity and frees mental space for solving high-level logical problems.

Why vibe coding tools are changing the rules of the game

The gap between a traditional IDE with autocompletion and a true vibe coding tool is substantial: in classic IDEs, AI is a guest; in modern vibe coding tools, artificial intelligence is the core. The interaction is bidirectional and deeply integrated. Asking the agent to “switch the whole app to dark mode and optimise API calls” means seeing it work autonomously across dozens of files, handling consistency and dependencies.

According to the latest industry data, these AI coding assistants can cut front-end development time by up to 80%, freeing teams from repetitive coding and allowing them to focus on product validation and user experience.

The rise of vibe coding tools is enabled by the maturation of Large Language Models (LLMs), which now feature context windows wide enough to read and understand entire repositories. When a runtime error appears, modern vibe coding tools act in three steps:

• they analyse the error log and identify the likely cause;
• they formulate a diagnosis based on the project context;
• they propose and apply an immediate patch, verifying its effect.

This fast and intuitive feedback loop is what truly defines the coding by vibes experience: not just aesthetics, but operational efficiency that allows hypotheses to be tested in real time. For companies, integrating vibe coding tools into their processes means producing more software, faster and with greater flexibility. The risk of generating low-quality code is real but is mitigated by integrated static analysis tools that enforce security and maintainability best practices.

Vibe coding tools: concrete benefits for businesses and product teams

For those running a company or a product team, adopting vibe coding tools is not a purely technical matter: it has a direct impact on time-to-market, on the ability to experiment and on development costs. The main observable benefits are:

• Drastic reduction in prototyping time: ideas, MVPs and proof-of-concepts can be built in hours rather than weeks.
• Stronger alignment between business and development: product managers and stakeholders can actively shape the product, reducing misunderstandings.
• Optimised innovation costs: ideas can be validated on the market before committing resources to a structured development.
• Freeing up time for high-value work: developers can focus on architecture, security and domain logic rather than repetitive tasks.

At Revelis we support companies and organisations in adopting these technologies in a structured way, embedding vibe coding tools into solid development processes, with strong oversight of code quality, security and data governance. This is the approach that turns AI speed into sustainable business value.

Comparative analysis: the best vibe coding tools of 2026

Not all vibe coding tools serve the same needs. The right choice depends on the use case, the desired level of control and the team’s skills. Below we present an overview of the best vibe coding tools of 2026, with their respective strengths.

Cursor: the vibe coding tool for AI-driven code editing

Cursor is a fork of Visual Studio Code that has quickly become the reference IDE for professional developers. Its distinctive feature is the deep integration of AI into the workflow: Cursor indexes the entire local codebase, allowing users to ask questions about any part of the project and to obtain coherent changes across multiple files in a single action. It’s the ideal choice for those seeking surgical precision without giving up the benefits of vibe coding.

Lovable: the ideal solution for full-stack web applications

Lovable is one of the most effective vibe coding tools for building full-stack applications from scratch. The platform turns text descriptions into complete React interfaces, also handling database logic and authentication. The principle is the purest expression of vibe coding: the user describes what they want to see and the tool “conjures” the application, making the line between design and development increasingly thin.

Lovable’s value emerges most clearly in cutting down the time needed to turn an idea into a concrete digital product. Thanks to a fully conversational approach, advanced prototypes, dynamic landing pages or working web apps can be generated even with limited technical skills: a decisive advantage for startups, innovation teams and founders who want to quickly validate a product hypothesis.

Replit Agent: the all-in-one development platform

Replit Agent is another undisputed leader among vibe coding tools. The platform has removed every barrier to entry: simply describe an application, even a complex one such as a marketplace or a data management system, and watch it be built, configured and deployed to the cloud in a single flow. Its ability to understand semantic intent is remarkable: in response to a prompt like “make the design more professional”, the agent doesn’t just change a colour but adjusts spacing, typography and visual hierarchy.

Replit Agent’s key strength is automating all the activities that traditionally require complex configuration: deployment, development environments and cloud integrations are managed inside the same workflow. This makes vibe coding accessible to designers, marketers and founders, while at the same time allowing product teams to speed up prototyping and focus on user experience.

Further reading: AI and vibe coding: building applications with LLM prompts

Bolt: the vibe coding tool for building web apps from a prompt

Bolt is one of the most innovative platforms for turning text prompts into working web applications in just a few minutes. Thanks to integration with advanced AI models, it allows users to generate interfaces, logic and full-stack components by describing in natural language what they want to build, with modern code immediately runnable in the browser. It is particularly popular with startups, designers and developers who want to quickly prototype MVPs and modern applications.

Bolt lets you modify and iterate the project conversationally, making the entire development cycle smoother. It’s an effective choice when the goal is to test an idea quickly, directly in the browser, without setting up local environments.

v0 by Vercel: generating modern interfaces with natural language

v0 by Vercel is one of the most interesting vibe coding tools for front-end work. It lets you create UI components and web applications simply by describing what you want, turning an idea into ready-to-use React code based on modern technologies like Tailwind CSS and shadcn/ui.

v0’s stated goal is to accelerate frontend development: thanks to its conversational approach, designers, developers and product teams can quickly iterate on layouts, dashboards and landing pages, modifying components in real time and obtaining highly realistic prototypes without having to write every single line of code.

For a global view, the table below offers a comparative overview of the main vibe coding tools of 2026, based on the analysis of market data (sources: CoderFile and Index.dev).

These data clearly show how vibe coding tools now cover every niche, from the rapid prototyper to the experienced software engineer, establishing themselves as a new family of professional tools rather than a passing trend.

Conclusions: the future of software development with vibe coding tools

Adopting vibe coding tools marks the shift from the era of mechanical code writing to the era of creative software management. This isn’t about losing technical skills, but about elevating them: using these tools wisely will become a fundamental skill, just as mastery of development frameworks has been over the past decade.

Whether the goal is launching a startup, accelerating product innovation or optimising internal processes, vibe coding tools are now essential companions for anyone aiming to innovate in the digital world. At Revelis we help companies and organisations integrate them strategically into their processes, combining AI speed with engineering reliability.

Want to understand how to introduce vibe coding tools and AI into your development processes? Get in touch with the Revelis team for a dedicated consultation: www.revelis.eu

L'articolo The best vibe coding tools for programming with intent proviene da Revelis.

The point is that AI regulation is uncharted territory. With the entry into force of the European Regulation , the AI Act, companies are required to meet precise standards on transparency, risk management, traceability and human oversight. Translated: it is no longer enough to innovate fast, you need to do it by following verifiable, demonstrable rules.

The AI Compliance Officer is the organisational answer to this transformation. We are not talking about a purely legal or purely technical role, but a hybrid one that brings together IT, legal, risk management and business. Its goal is to build an AI governance system that is sustainable over time, auditable and aligned with regulations.

For companies that want to grow in a solid, reliable and competitive way, having this role is no longer optional: it is a strategic lever.

What an AI Compliance Officer does in a company

Operationally, the AI Compliance Officer is the professional who ensures that AI systems comply with regulations, ethical standards and corporate policies. But what does this mean, in practice?

The first step is the mapping of AI systems already in use: identifying where and how algorithms, predictive models or automated systems are deployed, and classifying them according to the risk level set out by the AI Act. It is a crucial step, because it determines the regulatory obligations that apply.

From there comes risk assessment. The AI Compliance Officer defines processes to analyse bias, impact on fundamental rights, security and reliability of the systems. For high-risk applications in particular, strict procedures for control, documentation and continuous monitoring are required.

Another key area is technical documentation. The company must be able to demonstrate how its AI systems work, what data they use and which decisions they support: all of this requires a robust and constantly updated documentation infrastructure.

The work happens in close cooperation with the IT and data teams, to implement logging and auditing systems that guarantee transparency and accountability. At the same time, there is constant exchange with the legal department, to ensure alignment with regulations such as GDPR, NIS2 and other connected frameworks.

Finally, there is a front that is often underestimated: the cultural one. The AI Compliance Officer promotes internal awareness of the responsible use of AI, trains the teams and helps spread a culture of compliance and digital ethics.

In short, this is not a controller: it is an enabler of responsible innovation.

Business impact and competitive advantage

Thinking of the AI Compliance Officer only as a regulatory watchdog is reductive. To all intents and purposes, this is a value enabler for the business. In a context where AI is used to automate decisions, optimise processes and generate revenue, this role allows companies to scale AI adoption in a safe and structured way, reducing the risks that could slow innovation down.

The most interesting effect is precisely this: compliance stops being perceived as a brake and becomes a strategic lever. When AI systems are governed, documented and monitored, the company can speed up the rollout of new use cases without fear of regulatory breaches or reputational issues. This is especially true in regulated sectors such as finance, healthcare, insurance and public administration, where the balance between innovation and control is particularly delicate.

There is also a direct impact on stakeholder trust. Customers, partners and investors are increasingly attentive to how companies use AI, especially in terms of transparency and data management. A solid AI governance framework, led by an AI Compliance Officer, becomes a distinctive element that strengthens corporate reputation and improves perceived reliability in the market.

Last but not least, there is the reduction of indirect costs linked to non-compliance: fines, operational blocks, project rework, brand damage. From this perspective, the role should not be read as a cost centre, but as an investment that protects and enables long-term growth.

AI Compliance Officer and the AI Act: why this role has become essential

With the introduction of the AI Act, the first comprehensive European regulation on artificial intelligence, the AI Compliance Officer has gone from a nice-to-have to a real necessity. The regulation takes a risk-based approach, imposing different obligations depending on the impact of AI systems.

The complexity is significant. Companies must classify their systems, implement a risk management system, ensure human oversight, guarantee transparency towards users and be ready to demonstrate compliance through audits and inspections.

What makes the topic even more sensitive are the penalties: fines of up to EUR 35 million or 7% of global annual turnover, whichever is higher. Non-compliance, then, is not only a reputational risk: it is also a significant economic risk.

In this scenario, the AI Compliance Officer becomes the guarantor of compliance, but also a strategic player to avoid operational blocks, project delays or legal issues. And, not least, helps turn compliance into a competitive advantage: companies that can demonstrate reliability and transparency in their use of AI strengthen the trust of customers and partners.

Skills, profile and opportunities for companies

The AI Compliance Officer is a hybrid role and, precisely for this reason, hard to find in a single traditional profile. Many companies are rethinking their organisational structure or relying on specialised external partners.

The starting point is solid regulatory knowledge, especially of the European framework: AI Act, GDPR, cybersecurity regulations. But that is not enough: a technical understanding of AI systems, machine learning models and development processes is just as important.

On top of that come skills in risk management, auditing and governance. The AI Compliance Officer must be able to design processes, define policies and monitor compliance over time.

Equally important is the ability to communicate: translating complex concepts into operational guidelines that the business can actually use is a core part of the job, as is facilitating the dialogue between functions that often speak very different languages.

The demand for these skills is growing fast: AI compliance is no longer a niche topic, but a priority for organisations that want to use artificial intelligence at scale.

For businesses, all of this translates into an opportunity. Bringing in an AI Compliance Officer not only means reducing risk, but also accelerating AI adoption in a structured and secure way. In an increasingly regulated market, the ability to demonstrate compliance can become a real competitive differentiator.

Want to find out whether your company is ready to face an AI audit? Discover the AI Governance & Compliance services by Revelis and assess your organisation’s maturity level.

L'articolo AI Compliance Officer: who they are and what they do in a company proviene da Revelis.

For this reason, the results achieved year after year are a source of pride for Revelis, confirming that the company is moving in the right direction, with the ongoing goal of continuously improving working conditions and enhancing employee well-being.

Thanks to the consistency of its actions over time, Revelis having already reached an important milestone in 2025 with the HappyIndex® AtWork certification now celebrates a further leap forward: the achievement of the Platinum Medal, with an outstanding score of 479 out of 500, based on an anonymous survey in which the Revelis team shared their perceptions of their work experience.

This recognition rewards not a single result, but a structured and continuous journey toward excellence one that Revelis is proud to pursue.

Key performance areas

• Professional growth
• Work environment
• Management
• Recognition
• Purpose
• Sustainable development

Crescita professionale: percorsi chiari e sviluppo continuo

Vediamo nello specifico i risultati ottenuti nell’ambito della dimensione “crescita professionale”.

La crescita professionale in Revelis si conferma come uno degli elementi centrali dell’esperienza lavorativa, con un punteggio complessivo dell’85.2% che riflette un sistema strutturato, accessibile e orientato allo sviluppo delle persone. Il 90.9% del team dichiara di avere concrete opportunità per imparare e sviluppare nuove competenze, attraverso progetti sfidanti, attività di coaching, percorsi formativi, certificazioni e momenti di condivisione delle conoscenze. Questo dato evidenzia una cultura in cui l’apprendimento è continuo e integrato nelle attività quotidiane, non relegato a momenti isolati.

A rafforzare questa percezione contribuisce la chiarezza nei criteri di valutazione delle performance: l’86.4% delle persone afferma di comprendere come viene valutato il proprio rendimento, segnale di trasparenza e coerenza nei processi interni. Allo stesso modo, un altro 86.4% dichiara di avere visibilità su come sviluppare la propria carriera all’interno dell’organizzazione, in termini di responsabilità, progetti e opportunità di crescita. Questo aspetto è fondamentale perché consente alle persone di orientarsi, pianificare e sentirsi protagoniste del proprio percorso professionale.

Il dato relativo alla valorizzazione dei punti di forza (77.3%) introduce invece uno spunto di evoluzione: pur rimanendo positivo, suggerisce un margine di miglioramento nel riuscire a sfruttare pienamente talenti e inclinazioni individuali. Nel complesso, emerge un ambiente che investe in modo concreto sullo sviluppo delle competenze e sulla costruzione di percorsi chiari, ponendo le basi per una crescita sostenibile e condivisa nel tempo.

Ambiente di lavoro: benessere, sicurezza e collaborazione come fondamenta

Vediamo nello specifico i risultati ottenuti nell’ambito della dimensione “’ambiente di lavoro”.

L’ambiente di lavoro in Revelis si distingue per un livello di qualità particolarmente elevato, come dimostra il punteggio complessivo del 92%. Un risultato che riflette un equilibrio concreto tra benessere individuale, sicurezza e capacità organizzativa, elementi sempre più centrali nella costruzione di contesti lavorativi sostenibili. L’86.4% delle persone si dichiara soddisfatto del proprio equilibrio tra vita professionale e personale, segno di un’organizzazione che, pur operando in un contesto dinamico e orientato ai risultati, riesce a mantenere un’attenzione reale verso la qualità della vita delle persone. Questo dato si integra con un altro indicatore chiave: l’86.4% del team riconosce una collaborazione efficace tra i diversi reparti, confermando una buona integrazione interna e una capacità diffusa di lavorare in modo trasversale.

Particolarmente rilevanti sono i risultati legati alla sicurezza e al benessere complessivo. Il 95.5% delle persone afferma di lavorare in un ambiente sicuro e sano, che include non solo il rispetto delle normative, ma anche aspetti fondamentali come la sicurezza psicologica, la qualità delle relazioni, la presenza di spazi di dialogo e una gestione equilibrata dello stress e dei carichi di lavoro. Ancora più significativo è il dato del 100% relativo alla sicurezza fisica: tutte le persone dichiarano di sentirsi al sicuro sul luogo di lavoro, in un contesto che garantisce prevenzione, rispetto e assenza di comportamenti inappropriati.

Nel complesso, questi dati delineano un ambiente solido e affidabile, in cui le persone possono lavorare con serenità, sentirsi protette e costruire relazioni professionali basate sulla fiducia. Un elemento fondamentale che contribuisce in modo diretto alla qualità dell’esperienza lavorativa e, di conseguenza, alla performance complessiva dell’organizzazione.

Management: leadership presente, feedback continuo e chiarezza decisionale

Vediamo nello specifico i risultati ottenuti nell’ambito della dimensione “’management”.

Il modello di management in Revelis si distingue per solidità e capacità di supportare concretamente le persone, come evidenziato dal punteggio complessivo dell’86.4%. I dati mostrano un equilibrio efficace tra guida strategica, accompagnamento operativo e valorizzazione del contributo individuale. L’81.8% delle persone riconosce l’utilità e l’importanza del proprio lavoro per il successo dell’organizzazione, un segnale che il management riesce a trasmettere visione e impatto, collegando le attività quotidiane agli obiettivi più ampi. Questa chiarezza si riflette anche nella comprensione dei processi decisionali: l’81.8% del team dichiara di capire come vengono prese le decisioni, indicando un buon livello di trasparenza e accessibilità delle dinamiche interne.

Particolarmente rilevanti sono i dati legati alla relazione diretta con il proprio responsabile. Il 90.9% delle persone afferma di ricevere feedback utili, sia in termini di frequenza che di qualità, elemento fondamentale per favorire crescita, allineamento e miglioramento continuo. Allo stesso tempo, un altro 90.9% si sente supportato dal proprio manager, evidenziando uno stile di leadership basato su ascolto, disponibilità e presenza. Questo tipo di relazione contribuisce a creare un clima di fiducia, in cui le persone si sentono accompagnate nelle sfide quotidiane e sostenute nel proprio percorso professionale.

Nel complesso, emerge un modello manageriale coerente e orientato alle persone, capace di coniugare chiarezza, supporto e responsabilizzazione. Un elemento chiave per costruire engagement duraturo e favorire una cultura organizzativa solida e condivisa.

Riconoscimento: valorizzare il talento e l’impegno

Vediamo nello specifico i risultati ottenuti nell’ambito della dimensione “’riconoscimento”.

Con un eccellente 90,9% di soddisfazione totale, l’area del riconoscimento conferma come Revelis metta al centro il valore delle proprie persone. La quasi totalità dei collaboratori (95,5%) si dice estremamente soddisfatta dei benefit aziendali, mentre il 90,9% ritiene che la propria retribuzione sia adeguata alle responsabilità ricoperte. Oltre l’aspetto economico, emerge un forte senso di ascolto: il 90,9% del team sente che le proprie opinioni vengono prese in seria considerazione e l’86,4% si sente costantemente incoraggiato e valorizzato negli sforzi quotidiani.

Ragion d’essere: orgoglio e spirito di squadra

Vediamo nello specifico i risultati ottenuti nell’ambito della dimensione “’ragion d’essere”.

L’identità di Revelis e il suo scopo profondo convincono l’83% della popolazione aziendale. Un dato che spicca riguarda la qualità del clima interno: il 90,9% dei dipendenti è soddisfatto delle relazioni interpersonali, descrivendole come improntate alla sincerità, alla disponibilità e alla collaborazione. La fiducia nel team di gestione (leadership e gestione del cambiamento) è solida (81,8%), così come la capacità dell’azienda di evolversi a ritmi sostenibili. Infine, l’orgoglio verso i prodotti e servizi offerti (77,3%) rappresenta il motore che spinge l’azienda verso l’innovazione continua.

Sviluppo sostenibile: etica e responsabilità verso il futuro

Vediamo nello specifico i risultati ottenuti nell’ambito della dimensione “sviluppo sostenibile”.

La sostenibilità in Revelis è un valore concreto che raggiunge un punteggio totale del 90,9%. L’impegno verso l’ambiente è particolarmente sentito, con il 95,5% dei collaboratori che ritiene le attuali problematiche ecologiche adeguatamente integrate nella strategia aziendale. L’etica è un valore cardine anche nelle relazioni esterne: il 90,9% conferma l’assenza di conflitti di interesse o corruzione nei rapporti con clienti e fornitori. Internamente, la cultura dell’equità è predominante, con l’86,4% che riconosce pari opportunità per tutti, mentre il 90,9% si dichiara in perfetta sintonia con i valori, la cultura e il progetto strategico dell’organizzazione.

Un impegno verso un futuro ancora migliore

In conclusione, i risultati dell’indagine delineano il profilo di un’azienda dove il benessere e l’etica non sono semplici dichiarazioni d’intenti, ma realtà vissute quotidianamente. Il dato straordinario del 100% sulla sicurezza fisica e prevenzione dei rischi, unito al 95,5% di soddisfazione per l’ambiente sano e i benefit aziendali, conferma che in Revelis la cura della persona è la priorità assoluta. 

Con oltre il 90% dei collaboratori che si sente supportato dal management, valorizzato nelle proprie opinioni e in piena sintonia con i valori e la sostenibilità ambientale dell’organizzazione, la medaglia di platino HappyIndex® AtWork non è solo un traguardo, ma la conferma di un ecosistema vincente. Nonostante gli ottimi punteggi sulla crescita professionale (86,4%) e l’orgoglio verso i servizi offerti (77,3%), accogliamo questi dati come uno stimolo a migliorare ancora, continuando a investire nel talento e nelle relazioni per costruire, insieme, il futuro di Revelis.

L'articolo Revelis awarded the HappyIndex® AtWork Platinum Medal by ChooseMyCompany proviene da Revelis.

On the other, there is the burden of decades-old technological infrastructures layered and consolidated that represent both the beating heart and the operational “cage” of many institutions.

Within the context of digital transformation in banking, these legacy systems serve as the operational core but also as a major barrier to innovation.

At Revelis, driven by the mindset captured in our tagline #artificialintelligenceinaction, we recently managed the migration of a critical banking procedure shaped by 30 years of continuous development. Originally written in legacy languages such as PL/I and COBOL , it was transformed into a modern microservices architecture based on Java/Spring Boot and Angular.

Below, we analyze a concrete case of digital transformation in banking, where we converted a monolithic system into a modern, scalable solution ensuring quality through SonarQube  and achieving accurate data migration with AI-assisted ETL processes.

What is digital transformation in banking?

Let’s start by clarifying what digital transformation in banking actually means: it is the process of technological and organizational modernization through which financial institutions update systems, processes, and business models by integrating technologies such as artificial intelligence, cloud computing, and microservices.

This process enables banks to:

• improve operational efficiency
• reduce costs associated with legacy systems
• deliver faster, more personalized digital services
• ensure regulatory compliance (RegTech and AI Act)
• enhance data security and management

Digital transformation in banking is therefore a strategic step for competing in an increasingly digital and regulated market.

Examples of digital transformation in banking

Examples of digital transformation in banking include the adoption of new technologies to improve processes, services, and IT infrastructure.

Key examples include:

• migrating from legacy systems to microservices
• using AI for analytics and automation
• implementing chatbots and virtual assistants
• digitizing customer onboarding processes
• leveraging cloud computing for scalability and security
• integrating RegTech solutions for compliance

These initiatives enable banks to become more agile, efficient, and competitive in the digital marketplace.

The migration process in digital transformation

To better understand the approach taken, it is useful to look at how automation and human intervention were integrated at every stage of the transformation process.

Legacy systems: the weight of the past

Legacy banking software is not just “old” it is one of the main obstacles to digital transformation in banking. Over 30 years, multiple development teams maintained procedures written in PL/I and COBOL. While these languages were once pillars of enterprise computing, today they represent significant operational risks and are ill-suited for modern transformation needs because they:

• increase operational risk
• slow down innovation
• complicate integration with new technologies

The problem of technical debt

Technical debt is one of the biggest challenges in digital transformation. Thirty years of changes result in thousands of lines of code where business logic is often intertwined with outdated technical constraints. In many cases, original documentation has been lost or no longer reflects the reality of the code.

This creates a dangerous dependency on a small number of domain experts who understand these “black boxes.”

Migrating such a system does not simply mean “changing programming language” it means decoding three decades of business decisions, compliance rules, and complex calculation logic. This is where traditional approaches fail due to excessive costs and risks. This is also where Revelis’ vision comes into play.

Vibe coding and AI in banking transformation

As part of the transformation process, we adopted the Vibe Coding AI paradigm.

This approach enables:

• faster development
• improved code quality
• reduced dependency on legacy languages

What is vibe coding?

Vibe Coding is not just a trend it represents a fundamental shift in how developers interact with code. Instead of writing instructions line by line, developers engage with AI at a higher conceptual level. They communicate the “vibe” the intent, logic, and desired structure while the Large Language Model (LLM) handles the syntactic generation.

Prompt engineering as a programming language

Prompt engineering has become a key component in digital transformation. To extract logic from PL/I and COBOL, we used advanced prompt engineering techniques.

Rather than simply asking the AI to “translate,” we built structured prompting systems to guide deep reverse engineering:

• Contextualization: Providing the LLM with legacy language manuals to ensure accurate understanding
• Decomposition: Breaking large PL/I files into manageable logical blocks while preserving global context
• Iteration: Refining results through feedback loops, testing, and co-creation

Spec-driven methodology: the role of human validation

Human validation remains essential. The Spec-Driven approach allowed us to create an intermediate layer of functional “truth” before rewriting the system.

Generative technical-functional analysis

We used LLMs to analyze PL/I and COBOL source code and generate complete technical and functional documentation describing what the procedure does independent of the original language.

This analysis was not taken at face value. At Revelis, we see AI as an enhancer, not a replacement for human intelligence. Domain experts rigorously validated the output. Senior developers and business analysts ensured that the AI correctly interpreted even the most subtle business rules.

AI-Generated development plan

Once validated, we asked the AI to generate a detailed development plan, including:

• API definitions
• database structures
• integration logic between microservices

The AI effectively acted as a senior software architect, proposing the most efficient decomposition of the original monolith.

Data migration: AI-Assisted ETL processes

Data migration is one of the most critical aspects of digital transformation in banking. A banking system is nothing without its data. Thirty years of operations result in massive volumes of information stored in outdated formats or hierarchical/flat databases typical of mainframe environments.

As part of the transformation, this data must be migrated to modern relational databases.

We used LLMs to generate dedicated ETL (Extract, Transform, Load) procedures:

• Extraction: Understanding COBOL and PL/I record structures
• Transformation: Applying cleaning and normalization rules to ensure referential integrity
• Loading: Automating SQL script generation to populate new databases

This approach reduced database migration time by 80% and eliminated typical human errors in critical phases.

The new technology stack: microservices and modernization

Digital transformation requires modern architectures designed for scalability:

• Backend: Developed in Java with Spring Boot, breaking logic into independent microservices (e.g., customer data, accounts) to allow targeted updates
• Frontend: Angular replaced legacy character-based interfaces, significantly improving user experience and operational efficiency

Quality assurance with SonarQube

Code quality is crucial. AI-generated code introduces a key challenge: ensuring it is clean, secure, and free of vulnerabilities.

We integrated SonarQube into the development process to analyze every line of code for:

• Code Smells: ensuring readability and maintainability
• Vulnerabilities: critical for protecting sensitive banking data
• Technical Debt: avoiding long-term issues

This allowed us to objectively demonstrate that the new system is not only more modern but also superior in quality.

Efficiency and savings: the role of RegTech

Digital transformation is not just about technology it also involves regulatory compliance.

This approach ensured compliance with modern standards and the AI Act, while improving efficiency through automation of critical processes.

The AI Act introduces new requirements for transparency and governance. By documenting every step from reverse engineering to development planning we ensured full traceability and alignment with emerging regulatory expectations.

Conclusion: the future of digital transformation in banking

Compared to traditional manual migration, the benefits were clear:

• 50% reduction in overall development time
• 40% reduction in project costs

These results demonstrate that digital transformation in banking delivers tangible, measurable value.

Digital transformation is no longer optional, it is a necessity. The migration of PL/I and COBOL systems was not just a technical project; it proved that with the right methodology and a conscious use of AI, it is possible to unlock the hidden value of legacy systems.

Thanks to Vibe Coding, we turned IT archaeology into future-ready architecture. We demonstrated that:

• 30-year-old code can be understood and modernized rapidly
• AI, guided by domain experts, can produce reliable analyses and development plans
• modern technologies like Spring Boot, Angular, and microservices enable agile banking
• quality must always be measured and certified (SonarQube)

At Revelis, we continue to push the boundaries of innovation, bringing AI solutions across industries from healthcare to manufacturing and into the very core of banking systems.

If your organization is struggling with outdated systems that hinder growth, it’s time to change the vibe.

Want to start your digital transformation journey in banking? Get in touch with us.

Author: Massimiliano Ruffolo

L'articolo Digital transformation in banking: how to evolve with AI proviene da Revelis.

It is not simply a matter of installing a firewall or antivirus software, but of adopting a structured and systemic approach to protection. The ISO/IEC 27001:2022 standard represents the international benchmark for Information Security Management Systems (ISMS), providing a robust framework that enables organizations to identify, manage, and significantly reduce risks related to the confidentiality, integrity, and availability of corporate data.

Part of the ongoing digital transformation that companies must embrace also involves understanding the importance of ISO 27001 security. Today, this step means realistically assessing the numbers and the evolution of cybercrime. According to the recent Clusit 2024 report, global cyberattacks increased by 12% compared to the previous year, with particularly devastating impacts on critical infrastructures and small and medium-sized enterprises lacking adequate defenses. In such a constantly evolving threat landscape, certification should not be seen as a simple “badge” to display in a website footer, but as a competitive necessity and a demonstration of resilience. Implementing a strategy based on ISO 27001 security allows companies to demonstrate to partners, customers, and stakeholders that they have adopted rigorous measures verified by third-party bodies, raising the overall quality standards of the entire production chain.

What ISO 27001 security actually is and its core domains

Looking more closely at the standard, ISO 27001 security is based on a rigorous risk-based approach. But what does this mean in practical terms for a company? The standard defines international requirements for establishing, implementing, maintaining, and continuously improving an effective ISMS.

The structure of the standard is divided into two main sections:

• The main body clauses, which define organizational and governance requirements
• Annex A, which lists a set of specific controls designed to mitigate risks

With the 2022 update, ISO 27001 security controls were reorganized into four macro-categories: organizational controls, people controls, physical controls, and technological controls. This new architecture reflects the evolution of hybrid work and the widespread adoption of cloud computing, offering organizations a flexible tool to protect data wherever it resides.

Competitive advantages and ROI of ISO 27001 Security

Companies often perceive regulatory compliance as a passive cost, while the correct perspective is to view it as a high-return investment and a way to protect corporate value.

Adopting ISO 27001 security provides tangible benefits that directly impact financial performance. First, it significantly reduces the likelihood of a data breach, which according to authoritative studies by IBM can cost an average of $4.45 million per incident, including penalties and reputational damage.

Second, compliance with ISO 27001 security greatly simplifies alignment with GDPR, as many requirements of the European regulation are operationally addressed by the standard’s controls. Finally, it enhances the company’s reputation and opens the door to new markets, facilitating participation in both public and private tenders.

How to comply with ISO 27001 security

The journey toward full ISO 27001 security compliance is neither instantaneous nor purely technical. It is a methodological process that requires strong commitment from top management.

Risk analysis

The first essential step is Risk Assessment. During this delicate phase, the company must accurately map its information assets—hardware, software, data, and human expertise—and identify the threats and vulnerabilities that could compromise them.

Without a clear and quantified understanding of risks, it is impossible to implement ISO 27001 security measures that are truly effective and proportionate. Once risks are identified, the next step is the Risk Treatment Plan, where organizations strategically decide which risks to accept, reduce through technology, transfer via insurance, or avoid by modifying internal processes.

Creating the ISMS and ISO 27001 documentation

A crucial and indispensable component of ISO 27001 security is the proper management of system documentation. This is not about producing paperwork for its own sake or creating unnecessary bureaucracy, but about formalizing procedures and policies that must become an integral part of everyday corporate culture.

To achieve full ISO 27001 security compliance, organizations must prepare essential documents such as:

• The Information Security Policy
• The ISMS Manual
• The Statement of Applicability (SoA)

The SoA is the “master document” that lists which Annex A controls have been implemented and the technical reasons for their selection. Transparency and traceability of actions are fundamental: every employee must understand their responsibilities and know exactly how to act to maintain the organization’s ISO 27001 security posture.

The role of human training in ISO 27001 security

In cybersecurity, it is often said that the weakest link in the chain is not software, but the human being. For this reason, ISO 27001 security places strong emphasis on awareness and continuous training for staff at all levels.

Complying seriously with ISO 27001 security means educating every employee from the CEO to entry level operators about real risks such as phishing, the importance of secure password management, and the correct use of both corporate and personal devices.

A well-informed workforce represents the first and most effective line of defense against cyber intrusions. Implementing regular training sessions and “social engineering” tests is not merely a formal requirement of the standard, but a practice that transforms employees from potential vulnerabilities into active guardians of the organization’s information assets.

Monitoring and continuous improvement: the ISO 27001 cycle

Achieving ISO 27001 security compliance should not be considered a static milestone, but rather the starting point of continuous evolution. The standard is based on the well-known PDCA model (Plan–Do–Check–Act), which promotes iterative performance improvement.

Once technical and organizational controls are implemented, it is essential to monitor their effectiveness over time through regular internal audits and periodic management reviews. If these checks reveal nonconformities or new areas of weakness, immediate and documented corrective actions must be taken.

This dynamic approach ensures that the ISO 27001 security management system evolves alongside technological innovation and the emergence of new cyber threats, preventing corporate defenses from becoming outdated or ineffective.

Toward certification: the final audit

The final step in the ISO 27001 security compliance journey is the certification audit, conducted by an independent third-party certification body. This inspection process typically consists of two stages:

• Stage 1, mainly focused on documentation review and verification of system readiness
• Stage 2, which involves an in-depth on-site audit of the actual implementation of the declared procedures

During these sessions, the auditor will look for objective evidence that ISO 27001 security is being properly managed. Obtaining the official certificate is the ultimate proof of an organization’s operational maturity and professional reliability.

Conclusion

Investing in ISO 27001 security is now an essential choice for companies aiming for long-term sustainability and operational excellence. Protecting information does not simply mean defending servers; it means safeguarding customer trust and the stability of the company’s entire business vision. A crucial step toward sustainable, long-term growth.

L'articolo ISO 27001 security: what it is and how to comply to protect your company’s value proviene da Revelis.

AML obligations cut across multiple business functions: from Customer Due Diligence to transaction monitoring, from data collection and retention to reporting to the competent authorities. According to the most recent data released by Unità di Informazione Finanziaria (UIF), in the first half of 2025 more than 312 million transactions were monitored in Italy, with a total value of €15.538 trillion reported in anti-money laundering filings.

On the technology front, the global AML solutions market is also experiencing strong growth. It is expected to exceed $3.3 billion in 2025 and continue expanding in the coming years, driven by increasing regulatory complexity and the proliferation of digital channels.

Key regulatory obligations for banks and financial institutions

Supervised institutions are required to comply with a strict set of regulatory obligations. The main ones include:

1. Customer Due Diligence (CDD) and Know Your Customer (KYC)

Banks must verify the identity of customers and beneficial owners, collect up-to-date documentation, and assess each client’s risk profile. This is not a one-off process: it requires ongoing monitoring and periodic updates based on a risk-based approach, meaning controls are calibrated according to the level of risk.

Current AML regulations, including those issued by the European Union and transposed at national level, require documentation and risk assessments to be transparent, traceable, and continuously updated.

2. Transaction monitoring and suspicious activity reporting

Banks must implement monitoring systems capable of analyzing financial transactions in real time or near real time to detect anomalous or suspicious patterns. Prompt reporting to Financial Intelligence Units and other competent authorities is a binding regulatory obligation, subject to strict deadlines for filing Suspicious Activity Reports (SARs).

3. Data retention and audit trail

Regulation requires banks to retain a significant amount of information for several years, including customer data, due diligence documentation, transaction records, and reporting activities. This enables supervisory inspections and internal audits, ensuring transparency and traceability.

4. Risk-based approach and control governance

The risk-based approach requires that controls, resources, and technologies be proportionate to the institution’s exposure to money laundering and terrorist financing risks. This implies not only the adoption of advanced technologies, but also strong governance frameworks and internal procedures that are continuously reviewed and updated.

To effectively meet these obligations, banks increasingly rely on advanced tools such as Moneying, the platform developed by Revelis, which helps financial institutions comply with regulatory requirements while minimizing operational risks and improving overall AML process efficiency.

Emerging challenges in meeting AML obligations

Today, banks face numerous emerging challenges in complying with AML/CFT requirements. These stem both from the evolving criminal landscape and from constantly changing regulatory and technological frameworks. Such challenges can significantly affect operational effectiveness, costs, reputational risk, and the ability to respond to global threats.

The adoption of digital technologies and the growth of online transactions have made money laundering risks more sophisticated. Banks must manage ever-increasing data volumes, complex digital channels, and constantly evolving criminal models. As a result:

• Over 70% of AML platforms now integrate machine learning technologies, improving anomaly detection accuracy.
  
• NLP (Natural Language Processing) tools accelerate document analysis and the identification of risk signals in unstructured communications.
  

Key challenges in fulfilling AML obligations include:

Evolving criminal threats

Money laundering methods are becoming increasingly sophisticated and dynamic, including cryptocurrency-based techniques, synthetic identities, automated fraud schemes, and trade-based money laundering (TBML), which often evade traditional controls.

Legacy technology and data integration

Many banks still rely on outdated AML systems that lack real-time data integration and generate excessive false positives, leading to high operational costs and inefficiencies for AML analysts.

Data governance and digital onboarding

The digitalization of customer relationships (remote onboarding, mobile banking) increases the volume of data to be monitored and complicates the management of high-quality, standardized data for due diligence and risk assessment.

Regulatory evolution and complexity

The regulatory landscape is becoming increasingly complex, with new rules requiring continuous updates to AML programs and potential overlaps across jurisdictions.

Human resources and skills gap

A shortage of professionals specialized in AML, analytics, and emerging technologies represents a major obstacle to effective compliance.

Compliance costs and operational sustainability

Maintaining robust AML programs is costly. Investments in RegTech, AI, real-time monitoring, and specialized staff significantly impact banks’ financial performance.

Reputational risks and sanctions

Failures in AML compliance can result in substantial fines, reputational damage, and loss of customer trust.

Technology and solutions for AML compliance

Emerging technologies are transforming the way banks and financial institutions address AML obligations. Artificial intelligence, machine learning, and advanced behavioral analytics make it possible to:

• Improve transaction monitoring accuracy by identifying complex patterns and reducing false positives;
  
• Automate routine tasks such as risk classification, alert generation, and case management;
  
• Optimize Customer Due Diligence (CDD) and Enhanced Due Diligence (EDD) timelines;
  
• Integrate heterogeneous data sources, including open-source intelligence, to gain a more comprehensive risk view.
  

This digital transformation not only strengthens regulatory compliance, but also enhances operational resilience and reduces costs associated with manual controls.

Revelis has developed Moneying, a platform that combines Machine Learning and Deep Learning techniques to optimize compliance activities in AML controls and risk management. Through advanced Text Analytics, the platform also enables automated processing of written customer communications, streamlining the management of complaints, claims, and interactions with investigative authorities.

Revelis solutions fit into this ecosystem as advanced, modular compliance technologies designed to address AML obligations in an effective, scalable, and fully integrable way within existing banking systems.

Key benefits include:

• Intelligent automation of AML processes: Automated AML workflows reduce manual errors, accelerate response times, and allow compliance teams to focus on higher value-added activities.
  
• Governance and risk management dashboards: Comprehensive dashboards support strategic decision-making and help meet supervisory authorities’ transparency requirements.
  
• Flexible compliance with continuous regulatory adaptation: AML regulations evolve rapidly. Revelis solutions are designed for modular updates, enabling institutions to remain compliant with minimal IT intervention and operational disruption.
  

Conclusion

Banks operate in a rapidly evolving AML environment characterized by:

• Increasingly sophisticated and digital financial crime;
  
• Legacy technologies that are difficult to modernize;
  
• Complex, multi-layered regulations;
  
• A shortage of specialized expertise;
  
• Rising compliance costs;
  
• Significant reputational and sanction risks.
  

Responding to AML obligations is not merely a regulatory requirement it is also a strategic lever to safeguard financial integrity, mitigate reputational risks, and demonstrate a tangible commitment to combating financial crime.

As digital transactions continue to grow and risk scenarios become more sophisticated, advanced technology solutions such as those offered by Revelis are becoming essential enablers for banks and financial institutions. Investing in intelligent monitoring systems, process automation, and advanced data analytics not only facilitates AML compliance, but also strengthens internal governance, reduces operational costs, and enhances an institution’s ability to navigate regulatory and market challenges.

L'articolo AML: what are banks’ obligations and how to meet them proviene da Revelis.

In this context, the AI Act represents a major opportunity for organizations that want to adopt AI responsibly, at scale, and in alignment with European values. The regulation’s goal is not to slow innovation but to create a trusted ecosystem that encourages adoption by citizens, businesses, and institutions.

The PwC Voice of the Consumer Survey 2024 involving over 20,000 consumers across 31 countries shows that trust in digital technologies, including AI, strongly depends on perceived control, safety, and accountability in the use of data and algorithms. In particular, consumers are significantly more willing to use AI in low-risk contexts (such as recommendations or informational support) while showing resistance to high-impact applications (like financial or healthcare decisions) when governance safeguards, human oversight, and rights protection are missing.

This means compliance with the AI Act becomes a competitive asset not just a legal obligation.

Operationally, the AI Act directly impacts key processes such as HR, marketing, customer service, credit scoring, healthcare, cybersecurity, and supply chain. Any system supporting automated or semi-automated decisions must be assessed according to regulatory risk criteria, documented in a structured way, and governed through proper controls.

What the AI Act is and why it matters for your company

The AI Act is a European regulation establishing binding rules for the development and use of AI systems, classifying them according to the level of risk they may pose to individuals, organizations, and society.

The framework is risk-based and distinguishes four categories:

• Unacceptable risk (prohibited)
• High risk (strictly regulated)
• Limited risk (transparency obligations)
• Minimal risk (free use)

This model makes the AI Act flexible yet structured, adaptable across contexts while maintaining high safety standards. For companies, the AI Act introduces concrete obligations in governance, accountability, data quality, human oversight, cybersecurity, and transparency. Another strategic aspect is its extraterritorial scope: the regulation also applies to non-EU companies offering AI systems to European users. In other words, complying today means aligning with tomorrow’s global standards.

From a competitive perspective, the AI Act reinforces a key concept: trustworthy AI is a business advantage. Companies embedding compliance into their digital strategy reduce legal risks while strengthening positioning, reputation, and long-term sustainability.

Who must comply?

The AI Act applies to all organizations that develop, distribute, or use AI systems in the European Union market, regardless of legal headquarters.

This includes:

• Software vendors and AI providers
• Technology startups
• Enterprises integrating AI into core processes
• Public administrations
• SaaS and cloud platform providers
• Organizations using AI for recruiting, marketing, fraud prevention, risk management, and customer experience

The impact is particularly relevant for SMEs. While compliance may initially appear complex, it actually helps structure more mature, reliable, and scalable innovation processes avoiding improvised solutions that generate technical, legal, and reputational risks.

Importantly, the AI Act assigns responsibilities not only to developers but also to “deployers” companies using third-party AI systems. Every organization therefore needs internal competencies to evaluate, monitor, and govern AI solutions, even when purchased externally.

Timeline, penalties, and non-compliance risks

The AI Act formally entered into force in 2024 but will be applied progressively through a multi-year roadmap extending to 2027, allowing companies to adapt gradually while still requiring structural governance transformation.

Key deadlines

• February 2025 — Ban on unacceptable-risk AI systems (e.g., cognitive manipulation, generalized social scoring)
• August 2025 — Rules for general-purpose AI models, including transparency, technical documentation, and systemic risk management
• August 2026 — Full requirements for high-risk AI systems in HR, healthcare, credit, education, and critical infrastructure

The regulation therefore represents a continuous transformation journey rather than a single compliance deadline.

Penalties

The AI Act introduces a strict sanction regime comparable and in some cases stricter than GDPR:

• Up to €35 million or 7% of global annual turnover for the most serious violations
• Up to 3% or 1% for lesser infringements

Sanctions apply to:

• Use of prohibited systems
• Non-compliant high-risk systems
• Transparency violations
• False or incomplete information to authorities

However, the risk is not only financial. Companies often focus solely on performance, time-to-market, and ROI, underestimating regulatory exposure. This can lead to indirect costs such as:

• Service suspension
• Customer loss
• Litigation
• Reputational damage

Authorities may also force the withdrawal of non-compliant AI systems from the market even if embedded in mission-critical processes. In a context where trust and digital sustainability are competitive factors, non-compliance becomes a growth barrier, not just a legal issue.

Key statistics on AI adoption and compliance

Recent data shows AI adoption is growing faster than governance maturity. According to Eurostat, in 2023 about 13.5% of European companies already used AI (over 40% among large enterprises). However, fewer than one third had structured policies on explainability, algorithmic auditing, and risk management.

Image source: Use of artificial intelligence in enterprises

An IBM–Ponemon Institute global study (Cost of a Data Breach 2025) found that 63% of organizations lacked governance policies to manage AI or prevent shadow AI proliferation, increasing breach risks and economic impact.

PwC Global Compliance Survey 2025 confirms compliance evolution is essential to unlock growth:

• 77% say regulatory complexity negatively impacts growth drivers
• Coordinated compliance improves decision-making, transparency, and company culture

These findings confirm the AI Act is a competitive driver influencing innovation and market positioning.

How to comply: 5 best practices

Adapting to the AI Act means rethinking the entire AI lifecycle around governance, accountability, and business value.

1. AI System Mapping and Classification: Create a complete inventory of all AI systems (internal, vendor-provided, SaaS-embedded). Classify each according to regulatory risk and impact on rights, decisions, and outcomes.

2. Governance, Accountability, and Documentation: Define roles, responsibilities, and structured technical documentation:

• Ethical development policies
• Dataset registers
• Algorithmic audit trails
• Human oversight procedures

3. Risk Management, Cybersecurity, and Data Quality: Bias, model drift, vulnerabilities, and poor data quality undermine reliability and compliance. Invest in data governance, continuous monitoring, and secure infrastructure.

4. Training and Change Management: Compliance requires cultural change. Train management, technical teams, legal teams, and decision-makers on responsible AI principles and regulatory obligations.

5. Harmonized Standards and Certifications: EU harmonized technical standards (CEN, CENELEC) support compliance demonstration, covering safety, data quality, robustness, transparency, and explainability.

Conclusion

The AI Act is not simply another tech regulation it is a structural shift in how AI is designed, governed, and used globally. For companies, it represents a call to move from opportunistic AI adoption to responsible and sustainable innovation.

Complying allows organizations to:

• Reduce legal and operational risk
• Increase stakeholder trust
• Improve automated decision quality
• Strengthen long-term digital business sustainability

Trust is also a decisive factor for AI acceptance ( 2025 Edelman Trust Barometer Flash Poll ): higher trust in transparency and value correlates with greater adoption willingness. In a trust-driven market, AI Act compliance becomes a brand positioning and competitive differentiation tool.

Ultimately, the AI Act should be viewed as a digital maturity accelerator. Companies starting today will be better prepared for future regulatory and technological evolution, positioning themselves as reliable leaders in the AI economy.

Organizations can rely on specialized consulting partners such as Revelis, where dedicated AI specialists provide the expertise and guidance needed to achieve compliance safely while enabling innovation.

L'articolo AI Act: how to prepare your company for the new regulation proviene da Revelis.

To address this topic, this article provides a clear and comprehensive overview of the meaning, objectives, and implications of the AI Act, the world’s first global regulatory framework for artificial intelligence.

The AI Act is the European regulation on artificial intelligence and represents the first global attempt to establish a comprehensive legal framework for the development, use, and commercialization of AI systems. Approved by the European Union in 2024 and entering into force on August 1 of the same year, the AI Act introduces an innovative risk-based approach to AI regulation, aiming to promote technological innovation without compromising fundamental values such as human dignity, privacy, and non-discrimination.

Understanding what the AI Act is therefore means understanding how the rules of the game will change for companies, developers, and AI users, which technologies will be subject to strict obligations, and which practices will be prohibited.

AI Act: what it is and what its objectives are

To answer the question “what is the AI Act?”, it can be defined as a European Union regulation designed to govern the use, development, and commercialization of artificial intelligence (AI) systems within the European market. It was approved in 2024 and entered into force on August 1, 2024. The regulation aims to establish clear rules to ensure that AI systems are safe, reliable, transparent, and respectful of individuals’ fundamental rights.

It is one of the first regulations of its kind in the world and has the potential to become an international standard for AI governance, similar to what the GDPR has represented for data privacy.

The AI Act was designed to balance innovation and the protection of rights in a rapidly evolving technological landscape:

• Protection of fundamental rights: safety, human dignity, freedom, and individual privacy.
  
• Accountability and transparency: clearer and more standardized obligations for AI developers and users.
  
• Incentives for innovation: fostering a single European AI market while supporting startups and SMEs.
  
• Regulatory consistency: avoiding fragmented national regulations and creating a common legal framework across EU member states.
  

Read the article: Vibe Coding AI: the pogramming revolution 

How the risk-based approach works

One of the key elements in answering the question “what is the AI Act?” is its adoption of a risk-based approach. Unlike uniform regulation, the AI Act does not impose the same rules on all AI systems. Instead, it classifies AI applications according to the level of risk they pose to individuals, society, and fundamental rights.

This model allows the European Union to focus regulatory obligations on the most critical use cases, avoiding unnecessary constraints on low-impact innovation while imposing strict controls where AI can significantly affect individual freedoms, safety, and equality.

1. Minimal or no-risk systems

Most AI systems fall into this category. These are applications that do not pose significant risks to fundamental rights or personal safety, such as:

• content recommendation systems,
  
• spam filters,
  
• AI used in video games or image editing.
  

For these systems, the AI Act introduces no new regulatory obligations, leaving full freedom of development and use. This choice reflects the EU legislator’s intention not to hinder widespread AI adoption and to promote the competitiveness of the European market.

2. Limited-risk systems

Limited-risk systems are those that can influence users without having a direct or irreversible impact on their rights. Examples include:

• chatbots and virtual assistants,
  
• text, image, or video generation systems,
  
• emotion recognition technologies in non-critical contexts.
  

For these cases, the AI Act introduces transparency obligations, such as clearly informing users when they are interacting with an AI system or when content has been artificially generated. The goal is to enable informed decision-making and reduce the risk of manipulation or deception.

3. High-risk systems

The core of the regulation concerns high-risk AI systems, which can have a significant impact on people’s lives. These include applications used in sensitive sectors such as:

• healthcare (diagnosis, triage, clinical support),
  
• human resources (recruitment, performance evaluation),
  
• credit and insurance,
  
• education and training,
  
• critical infrastructure and security.
  

For these systems, the AI Act imposes strict requirements, including:

• management and quality of training data,
  
• detailed technical documentation,
  
• system traceability and auditability,
  
• mandatory human oversight,
  
• conformity assessments prior to market placement.
  

For businesses, understanding what the AI Act is becomes not only a regulatory issue but also a strategic one, as it directly affects development processes, governance, and compliance.

4. Unacceptable-risk systems

Finally, the AI Act identifies a category of practices considered to pose an unacceptable risk and therefore banned, as they are deemed incompatible with the fundamental values of the European Union. These include:

• social scoring systems used to rank citizens,
  
• technologies that use subliminal techniques to manipulate human behavior,
  
• certain uses of real-time biometric identification in public spaces.
  

These prohibitions represent a clear stance: not all AI applications are considered legitimate, even if they are technically feasible. The AI Act thus establishes ethical and legal boundaries within which innovation must operate.

How to check compliance with the AI Act: official tools and self-assessment

With the entry into force of the European AI Regulation, many companies are asking how to verify whether their systems are compliant. While several online resources exist, it is essential to distinguish between indicative tools and legally binding procedures.

The AI Act Compliance Checker: the official tool of the European Commission

Among the available tools, the primary reference point is the AI Act Compliance Checker. Developed directly by the European Commission, this tool is currently available in beta and is part of the Single Information Platform dedicated to the regulation.

What it is used for:

• Clarifying obligations and requirements under the regulation.
  
• Helping operators identify which rules apply to their specific system.
  
• Offering an initial, interactive, and intuitive approach to assessment.
  

Important: Although it is an official resource, the website specifies that the tool does not constitute a “formal audit.” It should be considered an indicative screening and does not replace full legal advice.

Unofficial self-assessment tools

In addition to the Commission’s checker, several third-party self-assessment tools are available online. While useful for deepening understanding of the regulation, it is important to remember that no automated system can replace the formal Conformity Assessment, which is mandatory especially for AI systems classified as high risk.

How to proceed with a proper assessment

For those seeking reliable guidance today, the recommended path includes three key steps:

1. AI Act Service Desk: Use the European Single Information Platform as the official reference point for information and direct support.
   
2. Initial Screening: Use the Compliance Checker for a preliminary analysis of applicable requirements.
   
3. Specialist Support: Work with qualified professionals or notified conformity assessment bodies to obtain legally valid certification.
   

In summary, technology can help navigate the complex landscape of the AI Act, but full compliance requires a rigorous technical and legal analysis that goes beyond a simple online test.

Penalties and impact on businesses

We started by answering the question “what is the AI Act?”, but once it is understood, it is also important to know that violations of the AI Act can result in very significant penalties: up to €35 million or 7% of a company’s annual worldwide turnover, depending on the severity of the infringement.

This makes the AI Act not just an ethical guideline, but a real legal requirement for companies operating—or intending to operate—within the European market.

Today, AI increasingly permeates our daily lives: from healthcare to personalized advertising, from credit decisions to autonomous vehicles. Regulating these systems responsibly is essential to prevent discrimination, manipulation, or abuse. Moreover, policies such as the AI Act influence the behavior of global tech companies, which must comply with EU rules if they want to continue offering products and services in the European market.

Conclusion

In short, to briefly answer the question “what is the AI Act?”, it can be described as a pioneering European regulation that redefines how artificial intelligence must be developed, tested, and used in a safe, ethical, and transparent manner.

Its impact extends beyond the borders of the European Union and is already shaping corporate strategies, technological innovation, and citizens’ rights wherever AI is used.

L'articolo AI Act: what it is and why it matters for the future of AI proviene da Revelis.

Adopting advanced technological solutions is the answer to these challenges. Data confirms this trend:

• According to Istat, in 2024, the share of Italian companies with at least 10 employees using artificial intelligence technologies significantly increased, rising from 5.0% to 8.2%. This growth marks a clear and important step forward in process digitalization.
• Simultaneously, a McKinsey survey highlights the automation trend: 66% of companies had automated at least one business process by 2024.

These statistics demonstrate that automation and technological integration have become the fundamental pillars of modern business operational management.

In this dynamic context, we present PiGReCo, an information system developed to enhance the efficiency of business operational management by allowing organizations to supervise human resources, track activities and working hours, and monitor all key processes.

PiGReCo: the integrated architecture for excellence in business operational management

PiGReCo is an integrated and modular solution for business operational management, specifically designed to meet the needs of modern companies in terms of automation, cost control, and human resource management. Thanks to its microservices architecture, PiGReCo offers a scalable, secure, and highly flexible platform, accessible via web browser and mobile devices.

The solution allows for the end-to-end management of the entire project lifecycle, from the initial proposal phase to final reporting. The microservices architecture facilitates flexible management of business processes and allows for easy integration with other existing management systems.

Core functional pillars for business operational management

PiGReCo offers optimized business operational management through the following core functionalities:

• Comprehensive Project Management: Meticulous monitoring of every project phase, from commercial negotiation to production and reporting. This ensures complete and transparent control, essential for reducing delays and optimizing resource utilization.
• Strategic Human Resources (HR) Management: Tools for managing personal data, skills, holidays, and permissions. The system facilitates resource planning and allocation, allowing companies to optimize personnel usage and improve employee satisfaction.
• Real-Time Cost and Cashflow Control: Constant monitoring of costs associated with projects and resources. This supports more accurate and timely financial management, helping to identify areas of inefficiency and improve profitability.
• Activity Tracking and Reporting: Precise recording of hours worked for each activity, significantly improving cost control and overall operational efficiency.
• Advanced Document Management: Evolved functionalities for document management (metadata, versioning, and archiving) which facilitate secure access and information sharing, reducing the risk of errors and improving collaboration.

The strategic benefits of PiGReCo

PiGReCo in action: use case and criticality resolution

PiGReCo is the ideal solution for various business realities aiming to rationalize business operational management:

• SMEs needing a scalable and customizable solution to manage projects, resources, and financial flows.
• Production and Manufacturing Sectors requiring precise and real-time control over operational activities and costs.
• Companies with Distributed Teams needing a remote-accessible platform to facilitate collaboration and management.

The AMB Studio Case Study

AMB Studio, a company specializing in the development of business management systems for quality, environment, training, and workplace safety, chose PiGReCo to overcome operational inefficiencies. The implementation led to:

1. Centralized and fluid management of the entire project lifecycle (from commercial negotiation to reporting).
2. Accurate tracking of personnel hours and activities.
3. Precise and consolidated control over overall cash flow.

In summary, the platform allowed AMB Studio to integrate key processes and achieve a single, real-time view of business and financial performance.

Conclusion: AI as an accelerator for business operational management

The integration of advanced technologies, particularly Artificial Intelligence (AI), into management platforms like PiGReCo, is no longer a choice but a strategic lever. By leveraging AI’s ability to analyze large volumes of data, predict trends, and automate repetitive tasks, companies can free up valuable resources for high-value strategic decisions.

In a competitive environment that rewards speed, precision, and cost control, adopting AI and integrated management platforms is the tangible means to:

• Optimize the Operational Flow
• Enhance Competitiveness
• Ensure Sustainable Growth Over Time

Investing in PiGReCo means equipping your company with an advanced platform that strategically combines automation, innovation, and total process control. Your business operational management becomes more efficient, secure, and scalable, enabling decisions based on real data and improving overall profitability. For today’s businesses, PiGReCo represents the strategic solution to combine automation, innovation, and total control over business processes.

If you would like more information about PiGReCo, the solution developed by Revelis, contact us and one of our consultants will show you the benefits achievable for your organization.

L'articolo PiGreco: the business operations management solution proviene da Revelis.

In the technological landscape of 2025, we are witnessing a radical transformation in how we program. This isn’t just a trend: the Collins Dictionary selected it as one of the most significant words of 2025, underscoring the massive impact this approach is having across the entire software industry.

What exactly is Vibe Coding AI?

Vibe Coding AI is a software development approach that leverages advanced large language models (LLMs) to generate code based on natural language instructions. Instead of manually writing every line, the developer communicates their vision the project’s “vibe” to the AI, and the system automatically generates functional code.

The term “vibe” comes from the idea of conveying to the AI not just precise technical instructions, but the essence of what you want to create:

• Intention: What the code should accomplish.
• Context: Where and how it will be used.
• Style: The desired tone or structure.
• The Final Goal: The ultimate business objective.

It’s like explaining to an experienced colleague what you want to achieve without specifying every implementation detail.

For decades, programming meant translating human ideas into rigid syntactical constructs. Vibe coding inverts this relationship: the AI understands human language and translates it into code. Imagine needing to analyze sales data: instead of writing dozens of lines to open files, parse data, calculate statistics, you could simply say: “Analyze sales.csv, calculate totals by category, and generate a PDF report with charts.” The AI takes care of the rest.

How Vibe Coding AI works in practice

Vibe Coding AI is built on an iterative dialogue. The developer describes the goal in natural language: “I need a system that analyzes customer feedback and generates alerts for critical issues.” The AI then produces a complete implementation. The refinement process begins when the developer tests the code and provides specific feedback to the tool, repeating the process until the result matches the initial vision.

For instance, when building a book catalog app, you’d start with, “Create a web app for my books with title, author, and genre,” and then iteratively add: “Include real-time search functionality,” “Record reading dates with statistics,” and “Allow for personal notes and quotes.” Within a few hours, you can achieve a complete application that would have required days of traditional development time.

Vibe Coding AI: advantages and democratization

The most immediate benefit is an incredible acceleration: prototyping that used to take weeks can now be completed in hours. Experienced developers are reporting productivity gains of up to 300% on certain projects. But it’s not just speed; all the “boilerplate” work setup, configuration, standard features is eliminated, allowing experts to focus on the unique aspects of the project.

The most revolutionary impact is the lowering of entry barriers. For the first time, people with minimal programming backgrounds can create software prototypes. A designer can prototype interfaces, and a teacher can build tools for their classroom. This democratization brings a diversity of perspectives and innovations from those who possess domain expertise in other fields.

There is also a cognitive liberation: fewer interruptions to search for syntax or debug obscure errors means staying in the creative flow for longer. For learners, seeing quality code generated from their own requests becomes a personalized teaching tool like having a 24/7 mentor.

Vibe Coding AI: tools of 2025

The Vibe Coding AI landscape offers solutions for every need. GitHub Copilot excels at native integration into popular IDEs with smart code completions. Cursor is a full-featured editor built for Vibe Coding AI, capable of modifying multiple files and handling complex refactoring. Claude Code focuses on deep understanding and semantic analysis, making it ideal for enterprise projects.

“Agentic” platforms represent the cutting edge: Google Antigravity IDE allows AI agents to work simultaneously on different aspects under strategic supervision. Replit Agent offers browser-based development with zero setup, perfect for beginners. Specialized tools like v0 by Vercel generate React UIs from mockups, while Bolt.new creates full-stack applications in minutes.

Challenges and critical issues in Vibe Coding AI

Speed introduces significant risks. AI generated code can often hide vulnerabilities: insecure patterns, outdated dependencies, or missing validation. Precisely because it looks professional, we might let our guard down. A systematic approach is essential:

• Automated scanners to check for common flaws.
• Manual review of critical security sections.
• A rigorous security culture.

Architectural quality is another challenge with Vibe Coding AI. AIs excel at specific tasks but struggle with large-scale consistency. The risk is accumulating “invisible technical debt“: everything works locally, but the overall architecture is sub-optimal.

Clear standards are required to mitigate this:

• Regular code reviews to maintain quality.
• Scheduled refactoring to address structural issues.

There’s also the risk of dependency and skill erosion. A generation might grow up knowing how to describe what they want but not understanding how the underlying code works. The strategy here is balance: use vibe coding to accelerate, but dedicate time to programming “by hand,” understanding the generated code, and studying the fundamentals.

Vibe Coding AI has limitations in complex contexts: critical distributed systems, real-time applications, or safety-critical software. The sensible approach is hybrid: use vibe coding for well-defined modules, but maintain human control over architecture and integration.

The Future of the Profession

With Vibe Coding AI, the programmer of the future will be less of a “code writer” and more of an “AI orchestrator.” Like an orchestra conductor who doesn’t have to play every instrument perfectly but understands how to harmonize them, the programmer must understand architectures, patterns, trade-offs, and communicate effectively with AI systems.

New skills are emerging: advanced prompt engineering, architectural thinking, and critical validation of AI-generated code. New roles are being created: AI-Augmented Developer, Prompt Architect, and AI Code Reviewer. However, fundamentals like algorithms, data structures, debugging, and programming paradigms remain crucial and perhaps more valuable precisely because they become rarer. Soft skills are also becoming more critical: communication, teamwork, continuous learning, and ethics.

Conclusion

Vibe Coding AI doesn’t replace the programmer; it amplifies their capabilities. Value shifts from execution to design, from syntax to strategy. The most promising vision is one of deep collaboration: the AI excels at speed and pattern matching, while the human provides creativity, judgment, intuition, and ethical oversight.

Effective adoption requires a balance between AI and traditional skills, continuous training, a culture of quality, and ethical responsibility. For experienced developers, it’s a productivity multiplier. For beginners, it’s a learning accelerator that must not replace the fundamentals. For companies, it requires investment in training and governance.

If there’s a time to experiment, it’s now. Start with small projects, try different tools, and share your experiences. The future of programming is being written today, one conversation with an AI at a time.

L'articolo Vibe Coding AI: the pogramming revolution  proviene da Revelis.