“Innovation is a mindset”: from the Orbito platform to the future of integrated design

Alessandro Vitale, Head of Innovation at DVArea, explains how the project that won the BIM&Digital Award 2025 was conceived, what it involves, and which problems it solves. This is an opportunity to explore crucial themes such as corporate innovation strategies and the growing role of artificial intelligence in our sector.

DVArea recently won first place at the BIM&Digital Awards 2025 in the “BIM Initiative of the Year” category with the Orbito project. We asked Alessandro Vitale, Head of Innovation, to tell us how the project was created, what it does, and which problems it addresses. The interview also provided an opportunity to discuss other key topics, such as DVArea’s innovation strategies and the increasing relevance of artificial intelligence in our field.

Alessandro, in addition to being one of the company’s co-founders, you also serve as Head of Innovation. What does innovation mean for an integrated design firm like DVArea?

For DVArea, innovation is not just about adopting the latest technologies. It is a mindset – a continuous process aimed at radically improving the efficiency, quality, and sustainability of our projects. It is the ability to see opportunities to make a difference within challenging situations. As an integrated design firm, innovation manifests itself in the optimisation of the end-to-end process – from concept design to construction management and beyond, throughout the asset’s life cycle. It means overcoming the fragmentation of the supply chain and, at times, expanding it to create fluid, data-driven workflows, integrating diverse disciplines, and offering our clients solutions that not only meet technical requirements but also generate measurable added value.

How do you build and maintain a culture of innovation in a sector still strongly tied to traditional processes?

I must admit that in a traditionally conservative industry, it is challenging – resistance to change is high. We work on three pillars: training, experimentation, and recognition. We invest in training to ensure that everyone, from senior professionals to recent graduates, understands why change is necessary and how new methodologies make them more effective. Second, we encourage controlled experimentation. We allocate small budgets and dedicated time (our “Innovation Sandbox”) so teams can test new ideas directly on projects without fear of failure. Failure is treated as learning data. Third, recognition. Although this can be difficult amid daily operations, we try to celebrate innovative achievements to show that new ideas are valued and part of our DNA. Innovation must be everyone’s responsibility, not just that of the department I oversee.

Which skills do you consider essential to anticipate transformations in our sector?

Beyond traditional engineering and architectural expertise, three areas are crucial today:

• Data science and software development: In an increasingly connected and digitalised environment, the ability to collect, interpret, and use data – from calculation and simulation models or real-world sensors – is fundamental for making informed decisions and predicting outcomes.
• Advanced digital skills (Digital Twin, BIM, and Information Management): It is not enough to use the software; one must understand its integration potential and interoperability across platforms.
• Transdisciplinary collaboration and critical thinking: With integrated workflows, teams are becoming more multidisciplinary. The ability to communicate effectively, solve problems creatively, and remain open to diverse perspectives is essential for successful process innovation. Today’s innovator must be an interdisciplinary problem solver (and, to some extent, a cultural mediator).

Research and development are the engine of innovation. Does DVArea follow a structured R&D approach, or does innovation emerge more organically from projects? How do you choose which technologies or methodologies to invest in?

Our approach is hybrid. We cannot afford to wait for innovation to “just happen.” We maintain a formal R&D plan focused on strategic macro-areas, such as performance simulation, cognitive buildings, and generative AI. However, we also recognise that the most interesting challenges and the most brilliant ideas often emerge organically from projects. A complex technical issue in a project can, for instance, become the catalyst for a new methodology.

To decide where to invest, we use an “Innovation Scoring” system based on potential impact (how much it can improve quality or reduce costs or timelines), value and strategic alignment (how well it aligns with our values or long-term vision), and scalability (how broadly it can be applied across projects and sectors).

Only projects that exceed a minimum threshold receive dedicated funding, ensuring a balance between long-term exploration and immediate solutions for market needs.

We recently received first place at the BIM&Digital Awards 2025 in the BIM Initiative of the Year category for the Orbito project. Can you explain how this project originated, what it does, and which specific problems it addresses?

Orbito was created to solve a common problem: the difficulty of managing and accessing construction information easily and immediately during site supervision. Project documents are often numerous, follow an effective but unintuitive naming convention, and are organised in a traditional hierarchical folder structure that does not align well with the spatial logic of a construction site. Retrieving the correct document on site therefore takes time. Multiply this across all site inspectors and operational management teams, and it becomes an extremely time-consuming activity.

Orbito is our internal platform, developed in-house to support our Construction Management teams, acting as a “Digital Project Hub.” It brings together data from different sources (BIM models, documents, site reports, schedules) into a single web-based environment and manages the full approval cycle of documents transmitted from contractors to the construction management team.

The software allows users to navigate the 3D model directly from the browser and, by selecting a location or specific object, access the relevant documents sorted by pertinence to the active selection. The result is significantly reduced document search times and valuable time freed up for activities that truly require expertise and attention.

When discussing innovation, we cannot ignore the defining trend of the moment: artificial intelligence. Internally, you have created a dedicated team tasked with driving the adoption of AI within DVArea in a concrete and effective way. How are you approaching this? Which AI tools are you integrating into workflows, and which do you expect will become essential in the coming years?

AI is not a gadget – it can spark a revolution in productivity. Our AI team is moving in three directions: operational efficiency, structuring and preserving corporate knowledge, and AI for design. On the operational efficiency side, we are integrating AI tools for:

• Document analysis: We use LLMs (Large Language Models) to quickly summarise, query, and classify technical specifications, contracts, and regulations, accelerating due diligence analysis.
• Code generation: AI assists us in creating scripts and automation routines for BIM platforms and beyond.
• Specialised content support and production through custom AI agents.

Regarding corporate knowledge, our goal is to create an incremental, shared, protected, and accessible knowledge base – one that allows the company to reflect the technical expertise of the professionals involved in its projects and gives each professional access to this knowledge as part of the DVArea ecosystem.

In the coming years, I expect predictive AI tools for project risk management to become essential. These will analyse historical data (delays, cost overruns) to proactively alert teams to potential issues based on project phase, assignment type, and even client characteristics. As for AI-driven design, I believe it is still too early to discuss its full potential.

Do you see risks or critical issues in adopting AI within integrated design?

Absolutely. The main risks I see involve bias, data, and responsibility.

First, there is the risk of training AI on unbalanced historical datasets, which would replicate and amplify sub-optimal or non-inclusive solutions – and lead to dangerous design standardisation at the expense of creativity and real innovation. Second, AI is only as good as the data it receives. We must prioritise high-quality, well-selected datasets over general-purpose models trained on unclear sources. Intellectual property and the security of project data are also crucial concerns.

Finally, there is the issue of the “black box” of responsibility: if an AI algorithm makes an error that leads to damage, who is accountable? The designer who accepted the suggestion? The AI developer? The software provider who adopted the model? We need clear ethical and legal guidelines for AI use, ensuring that final judgement and responsibility always remain with the human professional.

Looking five years ahead, which transformation do you expect will have the most significant impact on how we design and build?

I believe that in the next 5–10 years, the most significant impact will not come from a single technology, but from the convergence of predictive AI applied to early-stage design – based on a Life-Cycle Thinking (LCT) approach – and Design for Manufacturing and Assembly (DfMA) enabled by the Digital Twin.

The LCT approach requires designers to consider the entire life cycle of an asset – from cradle to grave, or potentially cradle-to-cradle recycling – beginning with the earliest conceptual phases. AI has the potential to act as a process catalyst: when provided with historical project data (costs, timelines, performance, degradation), it can simulate hundreds of design scenarios, suggesting solutions that are not only efficient during construction but also the most economical and sustainable during operation and decommissioning. AI will elevate design to a level of “zero-loss” optimisation.

This optimisation will achieve its full potential only when combined with DfMA, which will transform the construction site into an extension of the factory where components are produced and pre-assembled. AI-assisted, life-cycle-optimised design will be translated directly into instructions for Offsite Digital Manufacturing, and DfMA will produce components with industrial precision and zero waste, ensuring that theoretical LCT efficiency is realised in the physical world.

AI will enable design and logistics optimisation, while DfMA will ensure that prefabricated components are produced efficiently and assembled on site with minimal waste and maximum speed.

Such a scenario requires strategic convergence between the specialised technical design capabilities of engineering and architecture firms and the digitalisation of the offsite manufacturing industry (DfMA – Design for Manufacturing and Assembly). This synergy demands a paradigm shift: design must not simply define the work but be inherently optimised for industrial production. Advanced information models (BIM and Digital Twin) allow engineering firms not only to generate complex geometries but also to parametrise the building into modular, prefabricable components optimised for assembly lines and robotics. The offsite manufacturing industry, in turn, provides continuous feedback to designers on constraints, tolerances, material costs, and production efficiency, closing the innovation loop.

The industrialisation of the construction sector will be the profound transformation that permanently changes how we conceive and deliver projects. The question remains whether the supply chain is ready to change. After all, as history has shown many times, the issue is not the technology, but cultural maturity.