When I finished my architecture studies back in the early 2000s (yes, I am that old...), I discovered what no one told me: a good, creative idea, a little talent, and a couple of sleepless nights aren't enough to make it in a parallel world of architectural practice outside of the creative bubble of academy. In order to make that idea a reality-and to ensure someone can actually build it as you envision it-you need to work really, really hard.

We used to tell ourselves we were artists, that suffering was part of the creative process, and that architects don't mature before they're 40.

Yet it took me far too many years to realize that struggle isn’t a necessity, regardless of the incredible projects I had the fortune to design (together with Ada Karmi-Melamede). By leveraging technology, we can work more efficiently, and at a higher level, without burning out.

The tools that every architect or even student has access to today were the stuff of science fiction not long ago. As these tools evolve and become accessible to non-programmers, the architectural journey is transforming. There are now more possibilities, and it's even more creative, as well as substantially less excruciating.

I still remember those endless hours spent refining designs by hand, adjusting plans manually, and wrestling with the limitations of outdated software. Back then, every detail required meticulous manual work, and any major change could mean starting from scratch. It was exhausting but also taught me resilience and problem-solving in ways that shaped my career.

Today, seeing young architects equipped with tools powered by AI, automation, and cloud-based collaboration fills me with awe. You can iterate faster, experiment without fear of wasting time, and push the boundaries of creativity. The process has become more about refining visions than getting bogged down by logistics.

So yes, I’m envious of you, young architects, for the path you’re about to walk—or run—or perhaps even fly, because with AI, the only limit is in your mind!

Full Disclosure: Nearly three years ago, I chose to join SWAPP and help build those wings for you. If you have the curiosity and passion to do things differently—smarter, faster, more accurately—reach out to us. The future is already here.

ISO/IEC 27001:2022 is an internationally recognized standard for information security management. It defines the requirements for establishing, implementing, maintaining, and continuously improving an Information Security Management System (ISMS). Certification demonstrates that an organization is compliant with these rigorous requirements, ensuring it can securely manage both its own data and data entrusted by customers and partners.

The standard's scope is comprehensive, covering a wide range of data types, including financial information, intellectual property, employee details, and third-party data. It provides a framework for identifying risks, implementing controls, and building a culture of security that evolves to meet emerging threats and compliance regulations.

Achieving ISO 27001 certification is a significant organizational effort. It involves participation across all levels of the company, from leadership to frontline teams, and includes thorough evaluations, ongoing monitoring, and multiple audits by accredited external bodies. This process ensures that an organization's security protocols are robust, adaptable, and aligned with the highest global standards.

For us, ISO 27001 is not just a checklist. It validates the rigorous security processes and practices we’ve built into our systems from the very beginning. Compliance is only one piece of the puzzle. At SWAPP.AI, we believe true security is about more than meeting standards—it’s about ensuring the integrity and trustworthiness of the solutions we deliver.

This is especially critical in the context of artificial intelligence, where data privacy often conflicts with the demands of machine learning. That’s why SWAPP.AI takes a different approach. Each of our AI models is bespoke, designed, and trained exclusively for the customer providing the data. Your data is yours, and it stays that way. We never train models using data from multiple customers. This isn’t just good privacy hygiene—it’s a fundamental principle for ensuring both trust in our technology and tailored results.

ISO 27001 certification is one part of our broader strategy for securing both data and AI. Security doesn’t stop at protecting sensitive information from breaches or leaks—it extends to how that data is used, processed, and ultimately leveraged to deliver value. Our commitment to security and privacy means we don’t cut corners. We don’t experiment with your trust. We build systems designed to protect it.

Why This Matters

• Security That Works for You: Your data is protected by systems and processes built to exceed global benchmarks.

• Privacy by Design: Our AI models are designed for you and you alone. Your data will never be used to train someone else’s model.

• Trust Beyond Compliance: Certification is a milestone, but our commitment to security and privacy goes deeper.

  
  

As we continue to innovate in AI, we know that trust is everything. Security and privacy aren’t just add-ons or features—they’re embedded in everything we do. ISO 27001 certification is a recognition of this philosophy, not the end of it.

Last week, SWAPP.AI CEO, Eitan Tsarfati and I attended the Trimble Dimensions conference in the vibrant city of Las Vegas. Hosted at the grand and luxurious Venetian Hotel, this event gathered over 7,000 attendees from across the AEC and infrastructure industries, making it a true showcase of Trimble’s leadership and influence. From insightful sessions to cutting-edge technologies on display, the conference offered a powerful glimpse into the future of our industry.

Expanding Horizons: The Global BIM Cloud

SWAPP.AI is now hard at work expanding our cloud services to integrate with more BIM providers and vendors, including Trimble’s SketchUp and Trimble Connect. Trimble Dimensions provided the perfect platform to meet the developers and technical leadership behind these tools, fostering meaningful conversations that broadened our understanding of the industry. These connections solidified our resolve to bridge gaps between platforms, ensuring that SWAPP.AI remains at the forefront of interoperability and innovation in the AEC space.

But this wasn’t just about tools—it was about rethinking the relationships between systems, workflows, and even the companies driving change. Discussions with innovators like Qonic, Snaptrude, and Skema.ai reinforced the idea that progress comes from collaboration. Together, we can reimagine how architects and engineers approach their work, creating solutions that put users first.

The Power of Open Standards

One of the most exciting themes at the conference was the push for open standards like IFC and IDS, particularly highlighted in sessions within the 3D Basecamp Track. These standards represent a future where tools, systems, and people can collaborate more seamlessly, breaking down silos and making it easier to focus on what matters—designing and building better spaces.

At SWAPP.AI, we’re not just following this trend; we’re driving it. Our soon-to-be-announced IFC schema will allow integration with any compatible system, further advancing our mission to make architectural design more connected, accessible, and efficient.

AI and Machine Learning in AEC

The use of machine learning and AI was another highlight of the event with many classes on its varied usage.  Several sessions highlighted the use of ML and AI to enrich models with BIM and IFC data (tag classification). These advancements align closely with our mission at SWAPP.AI, as we continue leveraging AI to automate tedious workflows and enhance design processes for architects and engineers.

A Celebration of Collaboration

The grand atmosphere of the Venetian Hotel and the impressive scale of the expo hall mirrored the ambition of the conference itself. It wasn’t just a gathering of technologies—it was a celebration of collaboration across sectors, platforms, and disciplines. For us at SWAPP.AI, Trimble Dimensions was a reminder that innovation happens when we connect the dots—between systems, ideas, and people.

Looking Ahead

We would like to extend our heartfelt thanks to the Trimble team for inviting us and for organizing such a phenomenal event. As we reflect on the conversations, insights, and connections we made, we’re more inspired than ever to lead the charge in shaping the future of AEC.

Stay tuned for more updates, including the publication of our new IFC documentation schema, as we take the next steps in our journey to revolutionize architectural design and construction. As always, we invite you to join us in this journey toward a more connected and innovative AEC industry.

Together, we’re not just imagining the future—we’re building it.

“One of the burning topics in the architecture world today is the issue of retaining good architects; harnessing automated tools and artificial intelligence may be the solution.”

By Eitan Tsarfati, Founder and CEO, SWAPP

One of the burning topics in the architecture world today is the issue of retaining good architects; harnessing automated tools and artificial intelligence may be the solution.”

By Eitan Tsarfati, Founder and CEO, SWAPP

Retaining up-and-coming architects poses an immediate and serious challenge for the entire real estate development industry and for architecture firms in particular. 

In a December 12, 2021 article, the New York Times wrote about architects at a major firm who were considering whether to unionize. Reading the many comments other architects posted about this article reveals a true crisis in the architectural design and planning industry. 

Industry leaders must recognize that the rate of architect defections to other careers is systemic. Let’s analyze the problem and then understand the role new AI and machine learning technologies can and should play in achieving a long-term solution.

What factors cause entry-level and associate-level architects’ discontent and even their abandonment of the architect profession? Low pay is always a factor, as are the long hours and slow career growth that architects experience at large and prestigious architecture firms. Additionally, slow career progression often follows three years of graduate study after the bachelor’s degree.

But there is yet another factor: the pervasive assignment to less-experienced architects of the stressful, unedifying design document and construction document development work. Architects want to design. Documenting the design so construction professionals can do their engineering and building jobs may be a necessary part of the process. Still, architects would be happier if someone else, or an AI technology, were to transform their designs into the CD for the architect to review and then stamp.

Traditionally, architectural firms have relied on having many “hands” working many hours to develop, complete and deliver sets of complete construction documents (CD). It’s a two-step process that starts with a set of design documents (DD) followed by developing the CD, and both of these steps require a high degree of accuracy and technical skill. Often, these steps are performed in a deadline-driven, pressure-cooker environment, because when the schematic design takes more time to complete than expected, the time frames for DD and CD development naturally must absorb the delay.

What do architects think about after spending long hours for low pay developing a set of construction documents? Do they find value in doing the CD development work? Or are they thinking about the 5-to-10 years they will spend in this role and wondering if it’s worth it?

With a limited number of new architects entering the field each year and the continual pressure from clients to deliver work ever more quickly, architects and architecture firms need a technology solution that relieves architects of the construction document design burden, while still getting this essential work done. The use of new AI technologies for these tasks will not only ensure accurate and quick generation of CDs, but will also result in higher retention rates of valuable architect employees.

Once upon a time, the prestige of architecture as a profession and the intrinsically rewarding nature of architecture attracted professionals by offering a career that spans several creative as well as technical disciplines. However, in today’s world of smart-everything, new entrants to the architecture profession are technically savvy. They expect the tools they use at work to be intelligent. They aren’t willing to spend multiple years doing tasks that a machine can do more quickly and with equal or better accuracy, while they wait for the opportunity to contribute to the aspects of architectural design that attracted them to the profession in the first place.

Just as they want to be able to plan all the details of a vacation road trip, then get in a self-driving car and relax while the car takes them where they want to go, architects want to spend the time allotted to their work creating the architectural designs, then “hand off” the design decisions to an intelligent tool that produces the necessary construction documents or revision options. They want relief from the tedious last step of the design delivery process.

Like other professions that used to assume the easy availability of a steady stream of new professionals willing to trade long hours in junior roles for bright futures as principals and industry leaders, architecture firms now face competition from “high tech”. The ranks of future architects — the creative, talented and bright individuals studying architecture and starting careers — may be wooed away by the higher pay, less oversight by older generations and a quicker path to the top that “high tech” offers.

Nevertheless, the good news is that “high tech” is also now solving the architect retention problem! New technologies enable architects to spend most, if not all of their time on design and planning work, and then to simply — and literally — “push a button” to produce clean, accurate and complete construction documents. In addition, architects can use these same technologies to make quick work of the time-consuming tasks of producing design alternatives to meet the needs of change requests and other “curve balls” that cause late-night work crunches.

By utilizing automated tools and artificial intelligence, these new technologies — of which Swapp is proud to be one — can transform architects’ planning decisions into architectural plans and deliverable construction document sets within minutes. No longer are long hours and tedious documenting tasks required.

Are you surprised that machine learning and artificial intelligence can now support your architectural work this way? Or maybe you want to ask why now or why did it take so long for technology to advance to this point. Of course, every advancement has a story behind it. For Swapp, the story involves a small, diverse group of architects, algorithm and AI developers and entrepreneurs from the world of existing computerized architectural tools.

Other teams and companies also know about the retention problem and are building tools for architects in the AI and machine learning space, allowing for collaborations as well as competition. Ready-to-use services, features and options made possible by these new technologies are here now to solve the needs of architects and architectural firms — and more exciting tools are on the way.

_______________________________________________

Eitan Tsarfati is a serial tech entrepreneur and Co-Founder and CEO of Swapp, an AI-based construction planning company which partners with architects to leverage the power of AI-driven platforms. He is an architect and a Harvard-Business School Alumnus who served as the former CEO of Autodesk Israel.

“If architects spent less time on manual processes, we could use our energies to explore new ways to innovate and improve our designs.”

By Eitan Tsarfati, Founder and CEO, SWAPP

“If architects spent less time on manual processes, we could use our energies to explore new ways to innovate and improve our designs.”

By Eitan Tsarfati, Founder and CEO, SWAPP

Over the past few years, various architectural construction planning technologies have emerged, changing the way we design. 

It seems inevitable that as the world goes through the process of digitization, the world of architectural planning will eventually follow. While many see this transformation as negative, I see it as positive. I’ve never understood why we are already using technology in our daily lives to save time and energy and not using it at the office to improve our productivity as architects.

Why should we, as architects, spend so much time on manual processes that can be automated? If we wouldn’t spend so much time generating output, we could use our time to explore new ways to innovate and improve our designs. Architects have always needed to embrace new technologies to keep up with the changing needs of cities and communities. Yet, the past year has illuminated the growing need to innovate the way that we work, live, and collaborate. Many emerging technologies will change the face of architecture as we know it. Let’s take a look at some technologies that are set to transform the field.

Generative Design

As I mentioned in my last piece, “How New Technology Is Enabling Architects to Realize Their Dream Designs,” generative design has been used by architects to explore hundreds of design sets, offering solutions to the challenges we often struggle with. Currently, most generative design software tools provide hundreds of options without screening them or optimizing them to match a particular construction project’s needs. I expect this technology will be further developed and enhanced over time, primarily through AI-powered and machine learning planning platforms. These innovations will help architects to free up more time to concentrate on other tasks.

Collaboration Platforms

Major developments in this field are collaborative software solutions aimed at helping architects take a leading role in the design and construction planning processes. Real-time collaboration software is already considered to be an essential part of the construction planning process. Today’s work environment has proved that communicating effectively and sharing data in real-time can transform how we approach the construction planning process.

Every architect’s planning cycle involves constant coordination with numerous stakeholders, and interaction with them often impacts our designs. For this reason, the latest AI technology in the field offers more than just a collaboration platform. It provides planning teams with access to the latest, most updated information. Additionally, it can quickly calculate and automate numerous iterations simultaneously, in hyper speed and complete transparency for all relevant stakeholders.

Artificial Intelligence and Machine Learning

In addition to Collaboration Platforms, BIM adoption and generative design, AI technology serves as the basis for our field’s next key technological developments. Architecture is an industry where creative processes suffer from countless obstacles on the way to the final design. I argue that the most powerful tool for helping architects regain control over the design process and re-inject creativity into the industry is using AI and machine learning technologies. These technologies already help architects and other key stakeholders to create a significantly easier process by providing access to countless data, models, interpretations of building environments, and cost estimates. These tools allow architects to create shorter, smarter, more creative design processes, leading to fewer design omissions or system clashes.

This stainless steel bridge is currently being 3D printed by MX3D; it will cross one of the best known canal’s in the heart of Amsterdam.

Additive manufacturing (AM)/or 3D printing

As an executive at Autodesk, I lead a software development team as part of the company’s Additive Manufacturing platform. Additive Manufacturing, most commonly referred to as 3D printing on an industrial scale, enables the digital to physically transform an object from the ground up. Using a layer-by-layer creation allows for complex and lightweight structures that could not be achieved by any other method. By using this technology, architects can convert their 3D digital model into instructions for the 3D printer. Despite the great promise of 3D printing technology, it is still considered one of the most controversial technologies because of its various technical constraints. I believe that this technology will significantly evolve in the next 5-7 years, but there’s still a long way to go before it becomes a standard in the construction industry.

Final Thoughts

After a transformative year, there is no doubt that architects are set to see the introduction of more and more technologies into their daily workflows. The industry’s many challenges are likely to be eased, if not solved, by technological developments. And these technological trends are undoubtedly opening up new opportunities for greater creativity, productivity, increase in efficiency, and optimization of our work processes for years to come.

The ability to adopt new technologies will soon become the bread and butter of innovative architects ready to embrace the future. I think it’s time we stop seeing ourselves as “worker bees” and start using our creativity and deep-thinking capabilities to explore new possibilities — this will help our industry evolve._______________________________________________

Eitan Tsarfati is a serial tech entrepreneur and Co-Founder and CEO of Swapp, an AI-based construction planning company which partners with architects to leverage the power of AI-driven platforms. He is an architect and a Harvard-Business School Alumnus who served as the former CEO of Autodesk Israel.

SWAPP is revolutionizing the architecture ecosystem with its AI-powered platform which automates architectural design and planning processes.

By Martyn Day - AEC Magazine March / April 2024

In a world swimming in AI-related hype, several CAD software firms are making serious progress in the race to eliminate workflow bottlenecks using new technologies. Martyn Day looks at the field of drawing automation and identifies some of its frontrunners

By AEC Magazine

Throughout their history, desktop CAD systems have been sold on the promise of delivering one overriding benefit: improved productivity when compared to manual drawing.

That makes sense, since productivity improvements are always sought by firms looking to save money and to increase their competitive edge. In these highly digitised times, the deployment of technology has become a key differentiator in the AEC world.

While it took twenty years for most AEC firms to move from drawing boards to 2D CAD, many like to think that the adoption of 3D CAD and BIM has been faster. In fact, that move has also taken the best part of two decades. And many of those firms using BIM tools have still not progressed as far as they might, remaining resolutely 2D-centric. On the other hand, who can blame them, when the primary deliverable of most contracts – and the most frequently cited target in legal wrangles – are drawings?

BIM was sold to 2D CAD users as a way to model their buildings and get automatic sections and elevations as a base for drawings, with the added benefit of coordinated documentation updates when model designs change.

In fact, what has happened is that the number of drawings produced has mushroomed. Many BIM seats are not involved in design at all, but instead focus on documenting the relatively poor automated output of 3D models.

A cynic might applaud the CAD software firms for increasing the costs associated with a documentation seat and driving appetite for complex document management systems to handle greater volumes of drawings. After all, many firms take the output from BIM tools such as Revit and perform refinements to drawing output in AutoCAD – the king of the 2D drawing world. However, this undermines the benefit of keeping both models and drawings in the BIM environment, breaking the links needed to coordinate updates to sections and elevations.

As documentation mushrooms, and clients increasingly demand BIM deliverables (even if they only do so because that’s what their consultant advises), the result is a heftier workload that consumes available resources and delivers a serious hit to the bottom line.

Many design IT managers have told me in confidence that they wish that drawings would simply ‘go away’. They would prefer the model to be the deliverable from which all data is extracted by contractors and project managers.

But here, they are at odds with the industry’s foremost institutions, such as the Royal Institute of British Architects (RIBA) and the American Institute of Architects (AIA), not to mention complex legal frameworks that are still largely predicated on drawings.

Here to stay

Another question I hear regularly is, “Why can’t AEC be more like manufacturing?” The misconception here is that once manufacturing designs move into CAD, the importance of drawings is greatly diminished.

But it might shock readers to hear that many manufacturing sectors – and in particular, automotive and aerospace – are just as burdened by the need to produce manufacturing drawings to accompany their 3D models, typically for reasons relating to fabrication and legal compliance. And this is the case even where parts are 3D printed directly from a 3D CAD model.

With that in mind, it’s safe to say that drawings are simply not going to ‘go away’. They will continue to be essential deliverables, although uses may change and their relevance in some areas may decline.

This is not to say, however, that there is nothing to be done about this situation. In fact, modern mechanical CAD (MCAD) tools do a much better job of automatically creating drawings and reducing repetitive tasks than today’s BIM tools, even for very complex parts and assemblies. That said, even with this progress, it’s estimated that engineers spend between 25% and 40% of their time refining drawings.

This is frustrating, because in modelling a building, a car or an aircraft, most design and engineering decisions have already been made. That makes it hard to justify excessive amounts of time spent creating 2D drawings from a model, a process that adds no real value to a project.

And as complexity increases, the case for drawings starts to fall apart. Take, for example, Frank Gehry, who couldn’t get any of his buildings made until he began using Dassault Systèmes Catia and McNeel Rhino. The drawings were so hard to understand that fabricators would bump up costs in order to accommodate the impact of inevitable misunderstandings. When Gehry’s practice switched to modelling buildings in 3D CAD and started sending Catia models to fabricators, he saw a corresponding drop in quotes and bids were suddenly aligned to within 1% of each other. As a result, his buildings were viable – but Gehry still produces 2D section drawings in AutoCAD in order to detail more standard aspects of designs. In other words, models offer clarity in situations of complexity, but for most buildings, simple rectangles are hardly likely to bust budgets.

Auto-drawings on demand

When I first met Greg Schleusner, HOK’s director of design technology, at a Bricsys (BricsCAD) meeting in Stockholm, Sweden in 2019, we quickly got talking about automated drawings. He explained to me that this was something the industry desperately needed, but that nobody seemed interested in developing the technology.

The case he put forward was clear. At that time, HOK was spending around $18 million per year on creating and managing drawings and construction docs (inclusive of staff costs, software and so on). Schleusner reckoned that, if the firm could automate 60% of the work associated with construction documents, or maybe 50% of the work associated with drawings, it would cut those costs in half. Even partial automation had the potential to deliver significant cost benefits.

While researching the topic, Schleusner discovered a Korean open-source project conducted for a building authority that focused on taking in IFC data and creating floor plan drawings for fire code review. Labels, text, drawing grids and dimensions were all added by the programme when the automated 2D drawings were viewed. He was impressed by the quality of the results. Everything displayed was dynamically created on the fly. It didn’t exist in the dataset.

“I think, at least from my perspective, the problem is we import all this other stuff into Revit. That is so much of our design effort, just to waste time to make drawings that we must make. So not only are the drawings themselves costly, but we also have this interoperability problem that needs to be solved. We have to send model data between design tools to make drawings. An open auto-drawing tool would allow design teams to stay in Rhino,” said Schleusner.

“What do you need to make drawings? Do you need an accurate model? If we solve drawing automation, we are going to have to make better models. If we make better models – hey, we have better models! We are going to have to improve what we model to get a better drawing. Right now, we have so much drawing work, that we all end up ‘faking stuff’ in drawings, just to get them out the door. I actually think auto-drawings is a very complementary idea to making better models.”

Since 2019, Schleusner has been bending the ears of leaders at many of the biggest CAD vendors, trying to spark their interest in auto-drawings. Now, with the advent of automation and AI, those vendors are scrambling to identify where might be best to apply new technologies. Since drawings represent ‘low-hanging fruit’, interest in auto-drawings has exploded.

Most of the early auto-drawing solutions will begin by offering configuration-based output (drawing templates). But Schleusner is keen to see work begin further upstream, at the project level. This would involve understanding what drawing sets are required by project managers and project architects, not just automating ‘the drawing’ but also automating project document sets. This would require the equivalent of HTML and CSS for drawing content, settings and how it is all put together.

“If the industry can solve this auto-drawing problem as a service, it could shatter the market into one thousand solutions, which is perfect. I don’t think you’ll need monolithic applications, because drawings are external and it’s an assembly process.”

In passing, Schleusner has also lamented that PDF is the ultimate industry deliverable, as historic constraints of standard drawings sizes 1:100/200 and so on limit the digital canvas. He explains that one of the reasons the industry makes so many drawings is because of the physical limitations of displaying text legibly within paper documents. “Couldn’t we just send one bloody big PDF drawing, which contractors never print out? If you can’t see something, then zoom in! While certain trades really liked this idea, it’s true that some want to print things out, which is a limitation. But if we can’t get the digital delivery of drawings right, how are we going to ever do the digital delivery of models?”

Powered by AI

Eventually, I suspect AI will feature in most auto-drawing solutions. To start with, there will be procedural AI, providing configurations and so on. From there, we will see more companies attempting to use AI to learn drawing layouts and perform automation functions, such as auto dimension, auto label, auto title block, auto table, auto grid and so on.

To figure out where all this might lead, it’s useful to first look at Swapp. Based in Israel, Swapp’s initial application of AI to Revit promised us a miracle. What it proposed was to take users from 2D sketches to fully detailed BIM, with all the drawings involved, in the time it took them to go and have lunch.

Along the way, Swapp would learn from past projects and then automate Revit detail models – a proposition that favours standard, rectangular, predictable buildings, such as student blocks, hospitals and offices.

That was the message delivered by Swapp’s chief science officer Adi Shavit at AEC Magazine’s NXT BLD 2023. More recently, I caught up with Shavit to discuss auto-drawings. As he explained, the company has pivoted its software engineering focus to deliver the auto-drawing component as a bespoke solution, as well as expanding to Canada and the UK.

Shavit explained how, in talking with clients over the past year, the number one feature that they wanted to know more about was auto-drawings, and not so much about the magic at work in turning 2D sketches into fully detailed Revit models.

However, to understand how to make a drawing, Swapp needs the model data. “All of our processing is done on our system in the cloud. We have a plug-in for Revit, which does the export and the interoperability part, but nothing really happens on the desktop. It talks to our system and sends us the model, then we generate the construction documents from that data and bring it back into Revit drawings,” Shavit explained.

“We are working with architecture companies, and we essentially say, ‘You can think of Swapp like you outsource drawing production to a team in Belarus or in India, but our delivery times for drawings are constant.’ Meanwhile, our customers are saying that they are invoicing their customers sooner, by one month or two months. And for us, that’s the name of the game. We’re charging based on project size.”

When it comes to rules/template-based automation, Shavit told me that Swapp tackles the output standards problem from the opposite direction, as every office has its own standards, and even within firms, teams have different standards. Swapp treats the standardisation of output wider and at much higher resolution. There is no uniform Swapp standard. It is derived from past projects, to generate drawings that are compliant with the specific customer’s way of doing things. This can start with Swapp looking at its past projects (both the BIM and the drawings), or it can be trained on projects currently in the works.

Shavit readily admitted that the documentation that is generated is not 100% complete. There are always special cases, special fire requirements for certain parts of the building and other external requirements. Documents will still need to be put past a senior architect for liability issues. But he claimed the company is trying to perform between 80% and 95% of the most tedious, time-consuming work, enabling skilled staff to focus their efforts on other aspects of projects.

At its heart, Swapp is a consultative, bespoke auto-drawing solution that uses AI. Company executives are keen to state that it siloes every client’s data and AI into their own results. From this, it sounds as if Swapp has clients already using its technology, even though it’s hard to understand what they do from the company’s website.

It will be interesting to see how Swapp’s output quality, speed and ‘completeness’ compares to Autodesk’s own in-Revit auto-drawing features (more on this ahead) when they eventually ship.

Conclusion

Auto-drawings is not a matter of if, but when. It’s also a question of establishing which offerings are any good. There are so many firms now researching this area that auto-drawings are going to be available in pretty much every tool out there, both old and new. But there will doubtless be differences between them, in terms of capability, cost and how they are hosted.

Swapp is taking more of a bespoke approach and will create an auto-drawings system bespoke to your firm’s particular needs.

As far as timelines are to be considered, Swapp has demonstrated some capabilities from its cloud AI and has customers now. However, I think we are looking at two to three years before we have a choice of mature, tried-andtested auto-drawings technologies on the market, either in your BIM weapon of choice, as an online service, or as a bespoke customisation.

BIM 2.0’s killer feature is not going to be cloud; it’s going to be automation. Auto-drawings won’t just improve the speed of drawing production. They will ultimately mean fewer skilled people being tied up in documentation. If used well, this technology will also mean fewer licences of expensive CAD and BIM software needed in each firm. However, I am sure there will be a new business model from software developers eager to ensure that revenue isn’t lost in return for the productivity gains delivered. The good news for customers is that fierce competition means there will be plenty of options.

“The Israeli startup’s solution streamlines the creation and management of architectural construction documents.

”By CTech

SWAPP raises $11.5 million Series A to help architects with AI platform“The Israeli startup’s solution streamlines the creation and management of architectural construction documents.”

By CTech

SWAPP, which has developed automation software for architectural construction documents, announced on Wednesday the closing of an $11.5 million Series A funding round. With this funding, the company has raised a total of $18.5 million since it was founded.

The Israeli startup’s AI driven platform streamlines the creation and management of architectural construction documents, enabling architects to save time and resources while maintaining high-quality output.

Founded by serial entrepreneurs, Eitan Tsarfati, Noam Gat, and Adi Shavit, the company is headquartered in Tel Aviv with offices in Houston.

The Series A round was led by Eurazeo, a global investment firm, and included participation from existing investor Entrée Capital. New investors joining the round included Activum SG Ventures, the venture investing arm of European real estate private equity fund, Activum SG, and XTX Ventures, the investment arm of leading algorithmic trading company XTX Markets.

"The product we developed at SWAPP tackles the unfairness I faced as an architect on a daily basis - the excessive amount of time spent on creating intricate plans, rather than concentrating on the design aspect, and the lack of compensation for the many hours I spent on each project," said Eitan Tsarfati, Co-founder and CEO of SWAPP. “Our main goal is to help our customers become more productive from the moment they start using our platform."

“In Swapp, Martyn Day finds a contender for the most audacious AI tool yet for automating detail design work and producing drawings.”

By Martyn Day, Co-Founder, AEC Magazine

Swapp: The Algorithmic Assistant“In Swapp, Martyn Day finds a contender for the most audacious AI tool yet for automating detail design work and producing drawings.”

By Martyn Day, Co-Founder, AEC Magazine

In AEC Magazine’s AI Special Edition we began our journey to better understand how artificial intelligence will impact design and construction. In Swapp, Martyn Day finds a contender for the most audacious AI tool yet for automating detail design work and producing drawings

Maybe I’m getting old, but the future seems to be coming faster at me every day. Swapp is a cloud-based application that can automatically generate an entire Revit model with all the necessary detail drawings, from a simple space layout and without any indication where doors or windows should be.

For a simple residential building, all this happens in the time it takes to get a coffee. For an office block, you might need to wait a little longer. After lunchtime, maybe. Either way, this is going to be game-changing — and it’s only just started.

Throughout 2022, this magazine has focused on identifying start-ups that look set to move the industry forward and deliver new productivity benefits. One thing that I have observed is a general acknowledgement of a move towards the ‘templatification’ of certain building styles. And most agree that this will be achieved through the use of solvers, algorithms, artificial intelligence (AI), machine learning (ML) and as yet undefined genius.

Four-year-old, Israel-based Swapp is on a mission to automate the drudge work of repetitive design, modelling and documentation when it comes to predictable building types.

We might talk emotionally about the design and construction of buildings as unique and discrete processes, but if you boil it down, these are mainly based on tried-and-tested recipes. In other words, they are driven by parameters and by common methodologies that operate within the constraints of building regulations.

Swapp breaks down this process and learns by analysing previous Revit models. It then formulates ‘recipes’ it can apply to subsequent projects. Once the system is trained, it can automate designs that range from simple schematics through to full sets of construction documents. It achieves this using an AI planning and documentation rule system, hosted in the cloud.

This start-up’s ‘secret sauce’, meanwhile, is its Design Decision Language (or DDL), which encapsulates the core rules of architecture. This is linked to user-specific data and libraries which contain furniture, rooms, families, materials and building details.

Starting with a grid and a set of Revit spaces, the code identifies where spaces meet; what wall construction and finishes are typically used for each use case; typical door styles; and the furniture load for each room type. The final output is a full, code-compliant Revit model.

But Swapp doesn’t stop there. It also captures the print set styles that you prefer, in order to create a complete set of construction drawings that are automatically loaded into Procore. Now, this system may not fare well with a Foster + Partners airport design, but for buildings that are predictable and boxy, such as residential units, student accommodation and some office designs, Swapp can do in a day what might take you weeks or months to achieve.

Origins and aims

Swapp co-founders CEO Eitan Tsarfati and chief science officer Adi Shavit are veterans of the AEC industry. Tsarfati started his career as an architect before moving into the technology business, he explains. His first start-up was Homestyler, where Shavit was also a cofounder. This company was subsequently acquired by Autodesk, which Tsarfati and Shavit both joined as part of the deal.

“At Autodesk, we got more and more responsibilities, more products,” Tsarfati explains. “It became the home and building platform, which I headed up. Adi became the head of algorithm, as his specialisms are AI and computer vision.”

Having worked at Autodesk, the pair felt that the solutions that the company was providing to architects were insufficient, he says. “We understood that either we were going to re-do Revit, which is not something that a start-up should think about, or that we could try to practically solve the problem with what exists today, with what we can add to the equation.”

The architecture industry gets overlooked by many entrepreneurs and venture capitalists, he says, because they mistakenly believe that architects don’t have any money. As a result, 80% of today’s start-ups in AEC focus on job sites and try to solve construction issues. “But that’s a mistake, in my opinion,” he says. As a former architect, he understands the upstream pressures on architects, the lack of time for drawings, the tedious aspects of the job.

“Architecture has many functions, from feasibility studies, test fits, schematic design, VDC, DCA, you name it. But construction documents are the most tedious work, and this is the part where architects spend most hours, from the DD to CD stage,” he says.

“I think this is what makes us different from the rest of the start-up ecosystem, because most of the ecosystem — and I’m excluding Higharc here — are mainly doing feasibility studies. We are not going to do another parametric design system; we hate the terms ‘generative design’ and ‘optioneering’. We’re a very solution-oriented platform for construction documents. This is what we do.”

Off the grid

Working through an example, starting in Revit, a typical Swapp building starts off with a grid layout. The architect then designates areas for rooms, spaces, corridors, lifts and so on. These room-bounding components create an adjacency diagram which indicate to the AI where walls should go.

“There are some algorithms that can generate building plans like this, but I don’t believe that this should be the work of an algorithm. It’s actually the planning part. It’s where humans can think and make important decisions,” he says. “I mean, it’s architects who talk to the customers. The algorithm doesn’t!”

The process starts with a schematic design, one for each project, he explains. For each project, there are data libraries and design decision roles driven by Swapp’s design decision language.

“For example, in multifamily, you might say that all the walls between the restroom and the living room will look like this and will belong to a specific Revit family. On one side, wall finishes are ceramics, and on the other side, you’ll have gypsum, or plaster, or whatever it is,” he says.

The industry is somewhat hooked on selling billable ‘‘ hours and charging clients for changes. A piece of software that can model and document in 45 minutes, what would take an architectural practice months to achieve, changes the rules of engagement.

The rules are specific to the way an architecture office works and to the type of project. A school design, for example, will work from different rules in the design decision language. “How do we know? We look at our client’s past models and how they have done it before. Swapp’s AI understands what kind of doors you put in this type of mid-rise, multi-family block, in this current multifamily building. We also have a lot of best practices already built in, should you not have any past models,” says Tsarfati.

A key aspect of AI, and its ability to learn anything, is that you don’t feed it rubbish. As the saying goes, ‘Rubbish in, rubbish out.’ But Revit users vary wildly in their capabilities and adherence to standards, so Swapp has developed a suite of tools to learn from even badly organised Revit models and understand what went wrong.

Once a schematic is loaded into Swapp’s cloud, where the company has its own BIM modeller, the AI planner gets to work. Model and drawing generation is automatic. Decisions about where windows and balconies go, for example, are made. Everything is done by the Swapp algorithm, based on the basic layout from the architect’s plans, plus past project data. (By the way, this frees up your Revit licence to go and do something else, such as create another space layout for another job.) Typical processing times are between 40 and 50 minutes. The results are then translated back into RVT.

The resulting building may not win any awards, but the model will be highly detailed, each corresponding space loaded out with furniture content as defined in standard layouts. While the model is typically code compliant, Tsarfati explains that the architect should still ‘be an architect’ and check the model for themselves.

“We have the option to do all the energy loads and simulate that. We produce a very detailed model. We can do load calculations, we can do environmental analysis, we can run it through anything that we want, because we know everything about this building, even to the sub-layers of the paint on a wall,” says Shavit. A model that takes 45 minutes with Swapp, including all the layout sheets, might take three months in the real world, using human effort, he adds.

“If you think about details,” Tsarfati explains, “basically it’s the solutions for a typical intersection of two materials in the building. This is what it is, roof and wall, wall and floor, window and wall. So again, we work with companies, we take their data and we add it to the system, so the next time you use it, we have the details ready to add.”

To date, Swapp has focused Revit workflows and seems to have clients mainly in the US. But the target BIM system doesn’t have to be Revit, according to Shavit. “None of our processing happens in Revit. It happens in the Swapp projects cloud system. We only use Revit as the input and output,” he says.

“We already have automatic conversions, import and export for IFC, and since our model is as detailed as a Revit model can be, it’s very, very rich. Not just modelling, many systems actually use a 3D model. They don’t need the sheets. So, we could export to any compatible system, if the business makes sense.”

A bold game

It’s early days, but Swapp is attempting to do bold, game-changing things here. While the company’s leaders talk mainly about automating construction drawings, they almost bypass the fact that they, by the way, do a large chunk of the architectural detail design too.

And while it might appear that the architect’s job is reduced to simply arranging some conceptual rectangles in 2D, the model they get back is still Revit, and fully editable.

It’s the drudge work that has been done. The model and design can still be finessed. Users also get to reuse the knowledge and effort that has been put into the creation of families. And, since Swapp has multiple clients, they also get to benefit from everything Swapp learns from the common ‘hive mind’ of the industry.

This is a start-up that throws up all sorts of questions. It’s a bit of a curve ball. After all, the industry is somewhat hooked on selling billable hours and charging clients for changes. A piece of software that can model and document in 45 minutes, what would take an architectural practice months to achieve, changes the rules of engagement — but it’s open to everyone, including your competitors.

And what happens when clients get wind of the fact that your practice uses AI to achieve new heights of productivity? Will they expect to see that reflected in your fees? And finally, what about jobs? In other words, many firms globally have too much work and too few staff, so an AI-driven boost in productivity could be a massive benefit. But at some point, firms need to consider what a technology like this means in terms of team size, if and when the world returns to some level of normality.

It will be extremely interesting to see where Swapp ends up and how much traction it gets along the way, and in which markets. Perhaps it will build its own market as word spreads? Or maybe it will get snapped up by Autodesk to keep the Revit customer base happy? Adi Shavit has an invite to come and speak at AEC Magazine’s NXT BLD event in London on June 20. We’ll be looking forward to hearing more on the company’s progress between now and then.

If Swapp hasn’t already given you enough food for thought, you might be interested to know that Daniel McKenzie, senior data scientist at Life Time, recently sent me an article from the MIT Technology Review. In it, we learn about how OpenAI has built an AI-based game playing bot, which watched 70,000 hours of people modelling in Minecraft. The technique it uses is called Video Pre-Training. This lets an AI neural network train itself just by watching humans, a step up from the trial-and-error reinforcement approach to learning. Researchers at OpenAI hope to use this to teach bots to achieve in 3D space what GPT-3 has done to imitate human text.

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Martyn Day

Martyn Day is AEC Magazine’s co-founder and consulting editor and has been writing about design and the business of CAD for close to 30 years.

t in your talent acquisition goals.

“The latest technological developments allow architects, for the first time, to take the wheel in the planning process.”By Eitan Tsarfati, Founder and CEO, SWAPP

How New Technology Is Enabling Architects to Realize Their Dream Designs“The latest technological developments allow architects, for the first time, to take the wheel in the planning process.”

By Eitan Tsarfati, Founder and CEO, SWAPP

Every architect on the planet faces the same challenge: The way you envisioned your design is pretty different from the final result.

If you ever felt that way you’re not alone. I remember the first time my office won a new project, I was excited to start the design process. Yes, I am not ashamed to admit that from day one, I thought about the shapes, the forms, the tone — and imagined how this new project will inspire others for the years to come. But, very quickly, from the first meeting with the owner, my dreams were met with the harsh reality of budget constraints, engineering requirements and a tedious process that squeezed out every ounce of creativity I had.

Sounds familiar right? Whether it’s a stadium, a museum or a multi-family residential project, the planning process is long and complex. There are too many hands in the pot. The owner, the different consultants (every year it seems that we see more of them don’t we?), financial advisors, and the list goes on. By the time it ends, you can hardly recognize your dream design.

But you all know that already.

In an AIA report, different stakeholders such as architects, owners and contractors were asked to rank the key drivers of uncertainty on building projects.

Alongside unforeseen site conditions, which is among the top three factors cited by all participants, architects ranked owner-driven changes and accelerated schedule as leading force for uncertainty in projects. Owners and contractors on the other hand pointed to the design team (design errors and design omissions) as a leading factor. Unclear project requirements at the outset, identified by all parties as the top driver behind owner-driven changes.

I would argue that the way to bridge the gap between our dream design and the demands of the different stakeholders like owners and contractors is to embrace technology that allows architects to gain more insight and control over the process.

There are several sets of data architects are usually missing in order to make necessary adjustments while protecting their creative vision in the planning process. Many times, they are not fully aware of the site’s requirements and limitations. Another major missing variable is the owner’s financial objectives and the calculations made to achieve them.

The end result is usually similar — architects end up spending too much of our time on tedious repetitive iterations and tasks, and when changes are required, they have to do it all over again.

Over the past five years, various technologies have been developed to help architects gain valuable insights and even help automate many of the SD-DD-CD tasks, specifically manual ones which offer architects no added value.

Generative Design

Many of you are already familiar with and use “Generative Design” tools. Generative design has been helping architects discover dozens and hundreds of designs which include sketch constraints and goals. They solve the need to create what some would call “boring” building designs which lack a “soul” or a clear design concept. One of the main challenges of generative design, raised by Daniel Davis in his article “Generative Design is doomed to fail”, is that it offers hundreds of options to choose from without screening and ranking of the options according to methods used by architects in their design process.

I expect this will be improved over time, especially when combined with what I call “top-bottom” analysis in the form of AI-powered planning platforms which will eventually help architects to free up more time, from the screening of too many design options to focusing on creative solutions.

AI-Powered Planning Platforms

When addressing the need to create space for creativity, time is important and like in many other industries, architects understand today that data (and the tools to analyze it) is king. If we want to take an active role and create space for our creativity then we have to approach the planning process differently.

One of the main technologically-driven developments in any industry has been the use of AI-powered platforms. In our industry, these platforms allow architects access to data and deep analysis which are pivotal in creating designs that fit their vision and design concept while taking into consideration the demands of all the other stakeholders in the process.

Remember the key drivers of uncertainty architects had to rank in the AIA report? Today, there are many software platforms that help bridge the gap between our dream design and the demands of the different stakeholders. They aggregate and analyze a tremendous amount of data to help architects collect more information on a site, gaining greater control over a project, and the different challenges that may arise along the way. In recent years, the number of relevant data sources has significantly increased, leading to new analytical tools which can help architects predict various considerations such as site challenges and opportunities, project costs by construction method, as well as architectural and MEP strategies by project type.

Using these types of technologies, architects can find a balance between their vision and their clients’ cost constraints. They can also take control by including their ROI goals, embedding them into each design and having an algorithm analyze and compare them to data sets. Architects can save a lot of time and effort in analyzing their designs, from energy efficiency to occupants’ wellbeing parameters in a click of a button.

For too long, architects have taken the back seat in the planning process, fulfilling, and sometimes struggling to meet, the requirements and needs of other stakeholders. The latest technological developments allow them, for the first time, to take the wheel in the planning process.

By embracing technology, architects will begin each project with more data, AI super-powers to analyze it, and greater overview of key requirements, enabling them to better serve their clients while protecting their creative space. The architecture industry is in the midst of a technological revolution — and the future has never looked so bright.

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Eitan Tsarfati is a serial tech entrepreneur and Co-Founder and CEO of Swapp, an AI-based construction planning company which partners with architects to leverage the power of AI-driven platforms. He is an architect and a Harvard-Business School Alumnus who served as the former CEO of Autodesk Israel.