With its stated aim of developing a next generation BIM tool to rival Revit, Motif’s initial offering was bound to be a small subset of what will be the finished product. In AEC Magazine, we have explained this many times before, but it’s worth saying again – the development of a Revit competitor is a marathon and all the firms that are out of stealth and involved in this endeavour (Qonic, Snaptrude, Arcol and Motif), will be offering products with limited capabilities before we get to detailed authoring of models.

Motif V1 is a cloud-based tool which aims to address a range of pain points in architectural engineering and construction workflows, particularly in the design presentation and review phases. From what we have seen of this initial offering, it’s clear that Motif has identified several features which you would typically find across a number of established applications – Miro, Revizto, Bluebeam, Speckle, Omniverse and many CDEs (Common Data Environments). This means that there’s no obvious single application that Motif really replaces, as it has a broad remit. Talking to CEO Amar Hanspal (read our interview), the closest application the company is looking to as a natural replacement for is Miro, which became popular during Covid for collaborative working. As it’s browser-based it works on desktop, laptop or tablet.

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Ideation assembly

The initial focus of the release is to enhance design review workflows by offering a more connected and 3D-enabled alternative to Miro. Users can collate 2D drawings, PDFs, SVGs and 3D models from a variety of different sources, to bring them into the Motif space for the creation of presentations, markup and collaboration.

The primary sweet spot is for collating project images and drawings into Concept presentations, using an ‘infinite canvas’ which can be shared with team members or clients in real time. Models can be imported from multiple sources and views snapshot, drawings from Revit added, material swatches for mood boards, images of analysis results, pretty much anything. These can be arranged collaboratively and simultaneously by multiple users and the software neatly assists in grid layout with some auto assistance. There’s also the ability to add comments for team members to see and react to.

Motif recognises that a data centric approach is essential in next generation tools. With this aim in mind, Motif borrows some ideas from Speckle, offering plugins for a variety of commonly-used design tools, such as Rhino and Revit. These plugins offer granular, bi-directional links to the cloud-based, collaborative Motif environment. One of the special capabilities is the live broadcasting of objects from Revit as they are placed, with Motif displaying the streamed model.

It’s possible to run Revit side by side with Motif, with Motif automatically synchronising views. As geometry is added to Revit it appears almost instantly in the Motif view. This is food for thought, as it makes live Revit design information available to collaborative teams. While this is Speckle-like there’s no need to set up a server or have high technical knowledge.

Motif facilitates granular sharing of information through “frames,” allowing users to select and share specific subsets of data with different stakeholders. The software translates data from native object models (e.g. Revit) into a ‘neutral internal object model’ (mesh and properties) which allows it to connect with different systems.
Buildings can be manipulated in 3D and there’s smart work plane generation. This might not be super useful right now, but we can imagine how it will play out once the BIM modelling tools get added in. For now, images can be applied to surfaces and freehand 3D markup and surface-based detection give the software an uncanny intuition for selecting surface planes and geometry when the mouse is near.

It’s possible to make markups to these ingested objects in Motif, and somewhat amazingly these comments can also be seen back in the Revit session. For now, though, there’s no clash detection or model entity editing available in Motif – its initial use is design review. Motif stores all the history at an object level, allowing users to go back in time to previous states of a project and see who changed what.

The product’s interface is wonderfully uncomplicated with only nine tools. The display feels very architectural, presenting ‘model in white’ with some grey shadowing.

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The data model

The underlying data model is important. Motif uses a ‘linked information model’ based on the idea that in AEC all data is distributed data. Instead of trying to centralise all the project information in a single system, which is what Autodesk Docs / Autodesk Construction Cloud (ACC) does, Motif aims to link data where it resides and assumes that no single system will have all the necessary information for a building. So instead of ingesting and holding all the data to be one version of the truth, somewhat trapping users in a file format, or cloud system, Motif will pull in data for display and reference reasons. In the future we guess it will be mixed with its own design information.
Motif is intended to be ‘pretty open’ according to the team, with plans to expose the API and SDK to allow users and developers access to extract and add their own data and object types.

At the moment the teams are developing plugins to connect Motif with various commonly-used BIM and CAD applications, including Grasshopper, Dynamo, SketchUp and AutoCAD, in addition to Rhino and Revit which are already supported.

Business model

At the early stage of most startups, having a sales force and actively selling an early version of an application is usually a low priority. Instead, many startups just seek early adopters for trial and feedback. Motif, while being in development for almost two years already has a small sales team and is actively selling the software for $25 a month per user. Hanspal says this is to ensure good discipline in software development, to provide scalability, performance, and responsiveness to customer feedback. The initial adoption is expected to come from companies looking to replace parts of their Miro workflow.

Conclusion

Motif fully intends to take on Autodesk Revit in the long term. CEO Hanspal realises this is a multi-year marathon, so while the team develops a modelling capability, it is utilising elements of its current technology to provide collaborative cloud-based solutions for a variety of pain points which they have identified as being under-serviced.

For now, the company aims to develop a cloud-based 3D interface for project information which will not necessarily replace existing BIM or drawing systems but will act as an aggregator and collaboration platform for those using a wide array of commonly used authoring tools. The software comes to market with an interesting array of capabilities, which may seem basic but provides some insight into what’s coming next – the bi-directional streaming between authoring tool and Motif, the deep understanding of Revit data, models and drawings, Revit synchronisation, connectivity to Rhino and smart interaction with model data all impress.

There may be some frustration with obvious capabilities that are currently omitted, such as simple clash detection between imported model geometry but we are sure this is coming as development progresses.

What Motif does, it does well. It’s hard to pigeonhole the functionality delivered when compared to any other specific genre of application currently on the market. Many will find it’s well worth having for the creative storyboarding alone, others may find collaborative design review the key capability. Those that can’t afford Omniverse might love the ability to have an application that can display all the coordinated geometry from multiple applications in the cloud for project teams to see and understand.

t’s important to remember that this is a work in progress and as the software develops its capabilities, it will expand into modelling and creating drawings. Its tight integration with Revit will be useful and reassuring
to those who want to mix and match BIM applications as the industry inevitably transitions to BIM 2.0.

Meanwhile, the Motif team continues to grow, adding in serious industry firepower. After hiring Jens Majdal Kaarsholm, the former director of design technology at BIG last year, the company has added Greg Demchak, who formerly ran the Digital Innovation Lab at Bentley Systems, as well as Tatjana Dzambazova formerly of IDEO. Demchak was an early recruit at Revit before Autodesk acquired it and Dzambazova was a long time Autodesk executive, deeply involved in strategy and development of AEC, reality capture and AI. It seems the old gang is getting back together.

Interview with Amar Hanspal, CEO, Motif

Martyn Day: For this first product, what was the rational in bringing out this subset of features. They seem quite disparate?

Amar Hanspal: What we are trying to do, over multiple years, is build out a system that you would call BIM, to provide everything you need to describe a building and create all the documents that are necessary to describe the building. There are four key elements, plus 1: modelling, documentation, data and collaboration. And then the plus one is scripting.

The data part is all about how it’s managed, stored, linked, represented and displayed for a customer, which is the user interaction model, around all of this. Scripting is just automation across all of these four things. And we have always thought about BIM that way.

We know people will react to the initial product because they see the user interface and think we are doing markup and sketching. But behind the scenes, these are just the two things that got ‘productised’ first, data handling and collaboration, while we build towards the other capabilities.

Our philosophy around data is, no matter how we store it, fundamentally, no system is going to have all of the data necessary for a building. So instead of trying, like ACC tries to centralise the information – and while you will always have some data in your system, I think the model we’re trying to bring to bear is a ‘link information model’, like the idea that you’re watching us bring with the plugins and the round tripping of the comments. We’re going to assume that data is going to stay where it is, and like the internet, we have to figure out a linking model, sharing model, to bring it together.

You can look at the app where it currently is, which features a couple of core concepts that we’re trying to bring to market – this distributed data idea, and then the second one is the user model on top of it, enabling sharing.

Martyn Day: You have been talking with leading AEC firms for two years. How will you go from this initial functionality to full BIM?

Amar Hanspal: We can’t wait ten years, like Onshape to Fusion to get all the capabilities in there. So what’s the sequencing of this? From sitting down and talking to customers, the design review process that they were implementing, we product we ran across the most was Miro. For design review many are using a Miro board. They would express frustration that it was just a painful, static, flat process. That’s where our ‘light bulbs’ went off. Miro is just collages and a bunch of information. Even when we become a full BIM editor, we’re still going to have to coexist with Tekla,  Rhino, Tekla, some MEP application. We actually have to get good at being part of this ecosystem and not demanding, demanding to be the source of truth for everything.

It gets us to the goal that we’re looking for, and we’re solving a user problem. So that’s how we came up with what we were going to do first, a Miro workflow mirror, and some companies are doing design interview using Adobe InDesign. Over time, we can become more capable of replacing some of the things that Bluebeam and Revizt

Martyn Day: With the initial release you have started selling the product, many start-ups put off developing sales to get early adoption?

Amar Hanspal: It’s good discipline. It’s like, eating your vegetables. When you ask people for money, you have to prove value. It’s good discipline for us to deliver something that’s useful to customers, and see them actually go through the process of making decision to spend money on it because they see how much it’s going to help or save them. That’s really obviously Martin, why we’re doing it. Just good discipline. Fundamentally, we want to make sure that we’re professional people developing software in a professional way, it forces us to be good about handing things like scalability, performance.

Read our extended interview with Motif CEO, Amar Hanspal

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Project Tandem, as it used be known, was initiated in February 2020, previewed at Autodesk University 2020, and released for public beta in 2021. Four years on, there are still significant layers of technology being added to the product, now focussing on higher levels of functionality beyond dashboards and connecting to IoT sensors, adding systems knowledge, support for timeline events and upgrades to fundamentals such as visualisation quality.

Tandem development seems to have followed a unique path, maintaining its incubator-like status, with Autodesk placing a significant bet on the future size of an embryonic market.

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For those following the development of Tandem the one thing that comes across crystal clear, is that creating a digital twin of even a single building — model generation, tagging and sorting assets, assigning subsystems, connecting to IoT, and building dashboards — is a huge task that requires ongoing maintenance of that data.

It’s not really ‘just an output of BIM’ which many might feel is a natural follow on. It has the capability to go way beyond the scope of what is normally called Facilities Management (FM), which has mainly been carried out with 2D drawings.

The quantitative benefit of building a digital twin requires dedication, investment and an adoption of twins as a core business strategy. For large facilities, like airports, universities, hospitals – anything with significant operating expenses – this should be a ‘no brainer’ but as with any investment the owner/operator has to pay upfront to build the twin, to realise the benefits in the long tail, measured in years and decades. This, to me, makes the digital twins market not a volume product play.

Tandem evolution

My first observation is that the visual quality of Tandem has really gone up a notch, or three. Tandem is partially developed using Autodesk’s Forge components (now called Autodesk Platform Services). The model viewer front end came from the Forge viewer, which to be honest was blocky and a bit crappy-looking, in a 1990s computer graphics kind of way. The updated display brings up the rendering quality and everything looks sharper. The models look great and the colour feedback when displaying in-model data is fantastic. It’s amazing that this makes such a difference, but it brings the graphics in to the 21st century. Tandem looks good.

As Tandem has added more layers of functionality the interface tool palettes have grown. The interface is still being refined, and Autodesk is now adopting the approach of offering different UIs to cater to different user personas, such as operators who might be more familiar with 2D floor plans than 3D.

Other features that have been added include the ability to use labels or floor plans to isolate them in the display, auto views to simplify navigation, asset property cards (which can appear in view, as opposed to bringing up the large party panel) and thresholds, which can be set to fire off alerts when unexpected behaviour is identified. Users can now create groups of assets and allocate them to concepts such as ‘by room’. Spaces can now also be drawn directly in Tandem.

Speed is also improved. As Tandem is database centric, not file based, it enables dynamic loading of geometry and data, leading to fast performance even with complex models. It also facilitates the ability to retain all historical data and easily integrate new data sources as the product grows. This is the way all design-related software will run. Tandem benefits from being conceived in this modern cloud era.

That said, development of Tandem has moved beyond simply collecting, filtering, tagging and visualising data to providing actionable insights and recommendations. From talking with Bob Bray, vice president and general manager of Autodesk Tandem and Tim Kelly, head of Tandem product strategy, the next big step for Tandem is to analyse the rich data collected to identify issues and suggest optimisations. These proactive insights would include potential cost savings and carbon footprint reduction through intelligent HVAC management based on actual occupancy data.

Systems tracing

Having dumb geometry in dumb spaces was pretty much the full extent of traditional CAFM. Digital twins can and should be way smarter. The systems tracing capability in Tandem simplifies the understanding of all the complex building systems and their spatial relationships, aiding operations, maintenance, and troubleshooting. By clicking on building system elements, you can see the connections between different elements within a building’s systems and see how networks of branches and zones relate to the physical spaces they serve and identify where critical components are located within the space. This means if something goes wrong, should that be discovered via IoT or reported by an occupant, systems tracing allows the issue to be pinpointed down to a specific level and room. Users can select a component like an air supply and then trace its connection down though subsystems to the spaces it serves.

Tandem is a cloud-based conduit, pooling information from multiple sources which is then refined by each user to give them insight into layers of spatial and telemetric data

Building in this connection between components to make a ‘system’, used to be a pretty manual process. Now, Tandem can automatically map the relationships between spaces and systems and use them for analysis to identify the root cause of problems. Timelines Data is valuable and BMS (Building Management Systems) and IoT sensors generate the building equivalent of an ‘ECG’ every couple of seconds. The historical, as well as the live data is incredibly valuable. Timelines in Tandem display this historic sensor data in a visual context. Kelly demonstrated an animated heatmap overlaid on the building model showing how temperature values fluctuate across a facility. It’s now possible to navigate back and forth through a defined period, either stepping through specific points or via animation, seeing changes to assets and spaces.

While the current implementation focuses on visualising historic data, Kelly mentioned the future possibility of the timeline being used to load or hide geometry based on changes over time, reflecting renovations or other physical alterations to the building.

Bray added that Tandem never deletes anything, implying that the historical data required for the timeline functionality is automatically retained within the system. This allows users to access and analyse past performance and conditions within the building at any point in the future, should that become a need.

Asset monitoring

Asset monitoring dashboards in Tandem are designed to provide users with a centralised view for monitoring the performance and status of their key assets. This feature, which is now in beta, aims to help operators identify issues and prioritise their actions. They will be customisable, and users can create dashboards to monitor the specific assets they care about This allows for a tailored overview of the most critical equipment and systems within their facility.

The dashboards will likely allow users to establish KPIs and tolerance thresholds for their assets. By setting these parameters, the system can accurately measure asset performance and identify when an asset is operating outside of expected or acceptable ranges with visual feedback of assets out of optimal performance.

Assets that are consistently operating out of tolerance or experiencing recurring issues can be grouped to aid focus e.g. by level, room, manufacturer. With this in mind, Tandem also has a ‘trend analysis’ capability, allowing users to identify potential future problems based on current performance patterns. The goal of these asset monitoring dashboards is to help drive preventative maintenance and planning for equipment replacement.

Tandem Connect

Digital Twin creation and connectivity to live information means there is a big integration story to tell and it’s different on nearly every implementation. Tandem is a cloud-based conduit, pooling information from multiple sources which is then refined by each user to give them insight into layers of spatial and telemetric data. To do that, Autodesk needed to have integration tools to tap into, or export out to, the established systems, should that be CAFM, IoT, BMS, BIM, CAD, databases etc.

Tandem Connect is designed to simplify that process and comes with prepacked integration solutions for a broad range of commonly used BMS. IoT and asset management tools. This is not to be confused with other developments such as Tandem APIs or SDKs.

The application was acquired and so has a different style of UI to other Autodesk products. Using a graphical front end, integrations can be initially plug and play, such as connecting to Microsoft Azure, through a graph interface. The core idea behind this is to ‘democratise the development of visual twins’ and not require a software engineer to get involved. However more esoteric connections may require some element of coding. Bray admitted there was significant ‘opportunity for consultancy’ that arises from the whole connectivity piece of the pie and that a few large system integrators were already talking with Autodesk about that opportunity.

Bray explained that Tandem Connect enables not only data inflow and outflow but also ‘workflow automation and data manipulation’. He gave an example where HVAC settings could be read into Tandem Connect, and a comfort index could be written, which was demonstrated at Autodesk University 2024.

Product roadmap

Autodesk keeps a product roadmap which has been pretty accurate to show the development of travel, given the regular video updates.

Two of the more interesting capabilities in development are portfolio optimisation and the development of more SDK options, plus the possibility of future integration of applications. Portfolio optimisation will allow users to view data of multiple facilities in one central location and should provide analytics to predict future events with suggested actions for streamlining operations.

Beyond the current Rest API (Now), Autodesk is developing a full JavaScript Tandem SDK to build custom applications that leverage Tandem’s logic and visual interactivity. In the long-term, Autodesk says it will possibly enable extensions for developers to include functionality within the Tandem application itself.

Conclusion

Tandem development continues relentlessly. The capabilities that are being added now are starting to get into the high value category. While refinements are always being added to the creation and filtering, once the data is in and tagged and intelligently put into systems, it’s then about deep integration, alerts for out of nominal operation at a granular level, historical analysis of systems, spaces and rooms, all with easy visual feedback and the potential for yet more data analysis and intelligence.

Bray uses a digital twin maturity model to outline the key stages of development needed to realise the full potential of digital twin technology. It starts with building a Descriptive Twin (as-built replica), then Informative Twin (granular operational data), then Predictive Twin (enabling predictive analytics), Comprehensive Twin (what-if simulation) and Autonomous Twin (self-tuning facilities).

At the moment, Tandem is crossing from Informative to Predictive, but the stated intent for higher level functionality is there. However the warning is, your digital twin is only ever as good as the quality of the data you have input.

Some of the early users of Tandem are now being highlighted by the company. In a recent webinar, Brendan Dillon, director of digital facilities & infrastructure, Denver International Airport gave a deep dive into how they integrated Maximo with Tandem to monitor facility operations.

Tandem is an Autodesk outlier. It’s not a volume product and it’s not something that Autodesk’s channel can easily sell. It’s an investment in a product development that is quite unusual at the company. It doesn’t necessarily map to the way Autodesk currently operates as, from my perspective, it’s really a consultancy sale, to a relatively small number of asset owners – unlike Bentley Systems, whose digital twin offerings often operate at national scale across sectors like road and rail. The good news is that Autodesk has a lot of customers, and they will be self-selecting potential Tandem customers, knowing they need to implement a digital twin strategy and probably have a good understanding of the arduous journey that may be. The Tandem team is trying to make that as easy as possible and clearly developing it out in the open brings a level of interaction with customers that in these days is to be commended.

Meanwhile, with its acquisition of niche products like Innovyze for hydraulic modelling, there are some indications that Autodesk is perhaps looking to cater to more involved engagements with big facility owners, and I see Tandem as falling into that category at the moment, while the broader twins market has still yet to be clearly identified.

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In the world of infrastructure design, traditional processes have long been plagued by inefficiencies and fragmentation. That’s the view of engineer turned software developer Andreas Bjune Kjølseth, CEO of Norwegian startup Infraspace. “Going from an idea to actually having a decision basis can be a quite tedious process,” he explains.

Four years ago, Kjølseth left his career in civil engineering consulting and founded Infraspace, to develop a brand new generative design tool for civil infrastructure alignments – road, rail or power networks. In his years as an engineer and BIM manager Kjølseth was left frustrated by the limitations of traditional processes. Civil engineers commonly must navigate multiple software tools, explains Kjølseth – sketching in one platform, generating 3D models in another, using GIS for analysis on land take and environmental impact, and then manually assembling, comparing and presenting alternatives.

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Infraspace aims to unify this fragmented workflow within a single, cloudbased platform. The software is primarily designed to tackle the initial phases of linear civil infrastructure projects, using an outcome-based approach, as Kjølseth explains. “Users can define where they want the generative AI engine to explore alternatives and define the outcomes, such as, ‘I want options with the least possible construction costs, shortest travel time or length, and the least land take in certain areas.’ Then the algorithm will quickly explore opportunities to make better solutions.”

The Infraspace cloud platform generates thousands of alternatives within minutes, enabling engineers to explore options they might not have considered if done manually.

Design options are displayed via an intuitive web-based interface, featuring a 3D model alongside an analytics dashboard with key performance indicators (KPIs) such as cost, route length, land take, and cut-and-fill volumes.

The system can also be used to assess the environmental impact of proposed designs, including carbon footprint, viewshed, noise, and which buildings or areas might be affected.

Based on this information engineers can quickly compare and evaluate multiple design alternatives, then use the software to refine designs further. As the software is cloud based, this makes it easier for multiple stakeholders to understand the consequences quicker, explains Kjølseth

“The typical project manager often has limited access to advanced CAD, BIM or analysis software. With Infraspace they can quickly log into their projects in their browser and see the 3D models together with the analytics instantly,” he says. “It’s also possible to invite external stakeholders into the project to explore a selected number of alternatives.”

Project seeds

To start a project, users can pull in data from various sources, such as Mapbox or Google, or upload custom digital terrain models, bedrock surface models, or GIS data.

The design can then be kickstarted in several ways. An engineer could simply define the start and end point of an alignment, then let the software work out the best alternatives based on set goals. Alternatively, an engineer can define geometric constraints—such as sketching a corridor or marking environmentally protected areas as off-limits.

Users can define where they want the generative AI engine to explore alternatives and define the outcomes, such as, ‘I want options with the least possible construction costs, shortest travel time or length, and the least land take in certain areas’ – Andreas Bjune Kjølseth, CEO, Infraspace

The system is not limited to blank slate designs. It can also import alignments from traditional infrastructure design tools like AutoCAD Civil 3D and use them as a basis for optimisation. As Kjølseth explains, some engineers are even just using the platform for its analytical capabilities, to get fast feedback on traditionally crafted designs. The software offers import / export for a range of formats including LandXML, IFC, OBJ, BCF, glTF, DXF and others.

Adaptability across geographies

Infraspace is not hard coded for specific national design standards, but as Kjølseth explains, the platform captures the fundamental mechanisms of infrastructure design. It allows engineers to define geometric constraints, set curve radii, specify vertical alignment parameters, and adapt to different project types including roads, railways, and power transmission lines. It can handle projects with varying levels of design freedom, from short access roads to expansive highway corridors.

Designed by engineers, for engineers

For civil engineers seeking to streamline their design process, reduce environmental impact, and explore more design options, faster, Infraspace offers an interesting alternative to traditional fragmented workflows. Most importantly, with a team combining civil engineering expertise and software development skills, it’s clear the company understands the nuances of infrastructure design.

While Infraspace is currently focused on early-stage design and optimisation, its ambitions extend beyond. “We will continue to add more features as we go,” says Kjølseth. “I see that generative design as a concept and the platform we have, can definitely be applied to many use cases — during the latter stages of a project, and to even more complex problems.”

Main image: The generative AI engine can deliver thousands of design options in minutes

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It is very difficult to gauge the impact of AI and Machine Learning (ML) on any specific AEC discipline. It’s made even harder when the applications that claim to be AI are in fact several different computing automation strategies compiled together, with AI contributing the least. This will remain the case for a long time as developers of automation tools will use the best / fastest computational strategies for the right problem, and AI may well not be the centre or main contributor to the magic you will see before your eyes. However, it will increasingly come into the mix.

We first talked with Augmenta in October 2022. At the time, the company didn’t have a shipping product but was making noises about the automation of building systems such as mechanical, electrical and plumbing (MEP). Many of the team, based in Toronto, Canada, were ex Autodesk-developers who were responsible for the generative design code that was impressively applied to Autodesk’s manufacturing-focused CAD tools – Fusion and Inventor. They had big ideas as to how generative design could be applied in AEC but couldn’t find any takers within that Autodesk division, so set up Augmenta and started working on the problem of building services.

I dream of wires

Augmenta has ‘shipped’ its first cloud product, aimed at wiring up electrical components in BIM models. The software is currently limited to USA projects, as the team has coded in US standards first. It automates the routing and coordination of conduit systems across an entire building, through multiple floors based on user-defined rules, with the specification of device and panel locations, no-go zones and run schedules.

When the BIM (Revit) model is uploaded, Augmenta wires up all the electrical components, puts holes through walls for conduit, models everything in 3D, and provides an estimated cost. It’s possible to run several strategies at once and compare the price difference. Typically, this would take an expert days or weeks. Augmenta does it in hours.

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Once the electrical design is completed this can be exported to Revit for editing, detailing and clash detection. As the solution is in the cloud, development is ongoing and will eventually expand out to other countries.

Augmenta is simultaneously working on its auto-plumbing application which may come out this time next year. It will be possible to run a solve for both wiring and plumbing simultaneously. Eventually, when MEP is ready, Augmenta could do the whole lot in one pass. However, obviously the results need to be checked by a professional and perhaps altered for reasons not yet built into Augmenta’s system.

Augmenta is one of the poster children for BIM 2.0. These expert systems, which are coming to assist professionals, rapidly crush specification and detail design times. HighArc is another example that has built an automated house detail designer and drawing production system for American residential house builders.

If you extrapolate what these applications can do today, ten years into the future, you should be able to realise that the AEC design space is going to look very different. The levels of industry knowledge that will be built into ‘intelligent’ software will mean smaller teams will become highly productive, with automation perhaps completing 90% or more of each discipline’s detail work.

Add in ten years development of conceptual AI design tools, autodrawings, digital fabrication strategies and we have to consider very different tech stacks and team skills within AEC. From an initial concept, it could be hours or minutes to get a fully detailed model, with drawings and costings.

Thoughts from the team

To coincide with the launch of the new product we had a wide-ranging talk with Francesco Iorio, CEO, Aaron Szymanski, co-founder and head of product, and Matthew Hernandez, VP of Growth.

Iorio spoke at AEC Magazine’s NXT DEV conference in 2023 (watch his presentation) and was part of our mainstage demonstration in 2024 showing a non-Revit BIM workflow (watch the presentation).

AEC Magazine: Why did you start with electrical?

Iorio: Electrical is actually the hardest from a technical perspective. It may be easier in the sense that electricity doesn’t fight gravity like water but other than that, from a purely computational geometric perspective, it’s by far the hardest because electrical systems are made from conduits.

The number of parts that need modelling are even ten times what you need for MEP. We aren’t aiming to output a diagram or a high-level conceptual model. We want to output everything, something that’s constructible. We generate miles of raceway in one shot. This isn’t an assistant, it’s an automated system.

To do plumbing we will have to consider pressure, easiest transitions. You need to consider pressure drops, differentials and we would have to do some simulation. And of course, you must think about slopes for drains, which are a constraint.

MEP, in terms of geometry and topology, is much easier if you think about it. There are these giant ducts that take up a lot of space but essentially with mechanical it’s all about performance. You need to think about flow rates, take into consideration thermal losses, noise, vibration. It’s something that would apply computational fluid dynamics too.”

AEC: What kind of benefit will Augmenta offer electrical engineers and Revit workflows?

Szymanski: At the moment we’re not producing 100% perfect designs. There’s still the need for human cleanup involved at the detail level. The system might add an extra bend here and there, and there could be a self-collision somewhere.

We’re tracking all this and reducing the incident of errors over time. Today we will get you that initial population, will get you from a model that has nothing, to something that has 80% and customers are going to have to clean up that model themselves. Over time the amount of human intervention will reduce. We kind of think of ourselves as like a self-driving car startup, trying to reduce the amount of human intervention.

We have a broad scope for electrical, we cover a lot of the details like supports and couplings and we will eventually detail that functionality providing a full BoM. We can wire up a small hospital in just three hours – that’s the whole design – and eventually we’ll get to the point where there’s effectively no clean up. That means zero to fully detailed BoM, fully coordinated, ready to build in just a couple of hours.

AEC: What data does Augmenta need to start modelling electrical systems?

Szymanski: Basically, there are three main inputs: Revit model with just the most basic setup in terms of electrical equipment, the conduit run schedule, which defines your ‘tos an froms’ and what you want to run between that equipment, along with the design rules.

We really want to be able to get to the point where it’s just requirements, just tell us how many lights are in the building, tell us what sort of loads are in different parts of the building, [then] we’ll place the panels, we’ll pick the equipment for you, we’ll route everything and coordinate everything.

Once we have the mechanical and plumbing, we just run all that concurrently, so you have a full MEP system, that’s fully designed and coordinated, just based off high-level requirements. We’re moving upstream.

Today the way that the industry works is by prioritising some systems over others, so mechanical has top priority, like ducting over plumbing. Ducting has priority over pressure piping and those together have priority over electrical, because electrical can go up down around etc. So electrical is effectively just routing around in whatever space it can find. It’s why we started there because we can solve that problem for them, without anyone having to be aware they’re using a radically new way of designing their systems. Once we get into mechanical and plumbing, we’re going to build those out all at the same time and at once solve the same problem in three or four hours.

We understand that iteration is an important part of the process and must support that feedback loop. Our system means you can go through two full iterations of the entire building in a day as opposed to that happening over the course of months. Now [at the moment] with each iteration it’s a whole rebuild, going from scratch every time which we know is not ideal, so we’re looking at user-defined iteration, whether users can lock parts of the design and keep everything else unlocked for the next iteration. But we want to be able for this to happen automatically. Every user might load in a new background model and the outcome is that everything is the same except for one duct. Our software should recognise that and assume everything else is optimal.”

AEC: We suspect that the makers of conduit, MEP and plumbing might be interested in Augmenta specifying their products?

Szymanski: We’re talking to the main providers of conduit, and there’s a bunch of conversations we’re having on that topic. The most straightforward interest is that they want to be included in our default library, they want to be in that end BoM.”

AEC: How will you sell Augmenta? Is it a SaaS service, on demand?

Szymanski: We have two ways to get to market at the moment. The first is we’re offering design services through a partnership with ENG. ENG is the largest big modelling firm in the United States. We are now running our software on their entire pipeline, so they are still kind of the front end from a consulting model. With the back end of it we do the solution generation, make the user models and do the final editing on top of them and deliver those to our customers, but we’re not expanding that right now.
We have been using our software long enough to have actually built buildings. Our first was an elementary school in Michigan, we have another school where construction kicks off soon too. We are just building a flywheel for ourselves, where we’re running on as many live projects as we can, learning and building a product to produce real value for the industry.

AEC: How does Augmenta use AI/ML?

Szymanski: We use a combination of methods; our solution generation pipeline combines machine learning and various algorithmics methods in different parts. Right now, from a machine learning perspective we’re training primarily not on customer sites or in customer models, but on our own models. So, for example, when we generate a design, we generate a number of designs, a user picks one of those and we record that preference. We start to learn what is a higher quality design and what is a lower quality design, and then obviously there’s where those additional edits are made.

We learn from those edits as well and all this is about driving internally a higher quality score reducing the amount of human intervention. So, there’s a machine learning component that’s really about fine-tuning our internal weights and biases to produce higher quality results. The other thing we are using machine learning for is site interpretation. We’re not training on customer sites, but we’re really interested in using machine learning to interpret the sites to understand what’s a bathroom, what’s an elevator shaft, so we’re starting to extract that context data sites so that there’s less and less human setup required at the front end.

The biggest challenge we face, and it’s no surprise at all, is how messy Revit models are. They are so inconsistently modelled; people are not using the right elements and categories correctly. It’s no surprise to anyone I know in the industry, but it causes a massive headache when you’re trying to programmatically make sense of that site.

We’ve done a pretty good job of that but there are still specific things that need to be defined like firewalls, as we shouldn’t be cutting through them.

AEC: To come out with a good solution for a design, you really need to make sure you have a good quality BIM model to start with. From talking with others, the rather random nature of quality and precision in architect’s BIM models is a problem.

Hernandez: Unfortunately, too many people don’t see the value in model fidelity or use the best practices and that’s pervasive in the industry. We see the way of changing this is by making people incredibly more efficient than they are today by automating and optimising the design.

When you control the design, you control virtually all the downstream workflows, even to the level of construction and constructability. We don’t want to just speed people up – that’s just one benefit – we literally want to transform the construction industry and change the 25 years of no productivity gains that has plagued our industry for many reasons.

When you control the design, which is essentially the data from which everything else flows, you unlock advances in estimation, in procurement, in construction in safety on the job site, because you can prefabricate more. We are partnering with people who model well, are into prefabrication, and are willing to spend time to use our innovative tool fully so they’re the ones who are going to become more efficient. We already know there’s a huge labour shortage gap in construction, let alone to get into BIM VDC.”

AEC: When people think of AI in AEC, they tend to think of Midjourney. How is Augmenta different?

Hernandez: Right now, customers are saving about 60% but that’s just literally the tip of the iceberg. We’re working on some incredibly hard challenges – geometry, clashes coordination, path choosing, all in 3D. This is very different to the LLMs of text-to-render.

And a lot of the solutions that are built for construction today only address the symptoms not the problem. Ultimately, multidisciplinary firms using this technology will be able to estimate within a percent, which is incredible, which makes that available to the rest of construction – lowest carbon emissions, embodied carbon lowers construction costs etc.

Business model

All this automation could transform the way AEC firms work, but it also has a huge potential impact on software firms. To date, software firms have charged per user per licence, or token-based systems for usage estimated over years. Automation systems are going to remove the need for many licences of software that firms rely on today. And yes, while others will say there will be new jobs, the correlation between automation and smaller design teams, and fewer licences is going to have real consequences in future decades. We asked how software firms like Augmenta are reinventing the software business model?

Hernandez: Our product is still very, very early. It’s not our goal to go out and sell a bunch of SaaS licences. The pricing model that we use is to measure as closely as we can how much value customers are getting out of our software. For example, like the 60% increase in speed, with routing, modelling, coordination and then we take a small percentage of that as a fee. So as our scope increases, our fee will increase, but we would still be leaving the user, whether that’s a services firm, an engineering firm, or contractor with 90% of the value that we create.

Conclusion

Augmenta is a fascinating addition to the design landscape and the team is taking on some very big challenges – not just by discipline, but by country; not just attacking incumbent systems and workflows, but by having to trial new business models.
We hope the team’s opinions have stirred some thoughts and ideas of your own, as to what is coming down the pipeline for this industry with automation. The key takeaway seems to be that for the AEC industry to fully reap the downstream benefits of these advancements, it must significantly improve the quality of its BIM models.

The post Augmenta’s productivity promise appeared first on AEC Magazine.

Finch is an early-stage feasibility tool. It was originally developed by architects as a bespoke inhouse plug in for Rhino to deliver data-driven massing, storey design, space planning and floor layouts. One thing led to another, and Finch became a company, a product and a bit of a legend soon after its initial public showing.

Pamela Nunez Wallgren (CEO) and Jesper Wallgren (CPO) gave a presentation at AEC Magazine’s NXT DEV 2023 . Finch has so far raised $3.1 million for development and after what seemed like a lengthy time in stealth, working with a limited number of clients (Herzog & de Meuron and White Arkitekter), has now emerged, ready to expand.

Finch currently supports Rhino, Grasshopper and Revit, and there is an Autodesk Forma link in development. It uses two key underlying technologies, a graph-based rules engine and an AI learning system for analysing and generating optimal floorplans.

The software analyses room relationships – where vertices represent spaces and edges show adjacency – exploring multiple iterations by considering concerns such as spatial efficiency and daylight optimisation. Architects can modify these space relationships and requirements and dynamically optimise space usage.

Small is the new big

As far as AI is concerned, it’s fair to say the established AEC software developers have produced more words than useful code. Meanwhile, the innovation is coming from start-ups like Finch.

Nunez Wallgren agrees, “It’s exciting being in this space right now. It’s been really tough for the big companies to innovate. I think that is the strength of being a small startup, with a small agile team – you have a mission, you’re going out to change something, to disrupt something that is difficult to rally around in a big company.”

It’s not just software companies facing difficulty though, AEC firms are also under pressure on fees and there have been several layoffs in construction, as well as insolvencies. Firms will need to look towards adopting productivity tools to become more efficient and to do more with less. Here the new generation of products like Finch have a role to play.

“To us, Finch is where architects and AI design together, and the together part is key to us. We believe that what architects really need is a copilot, rather than autopilot.”, explains Nunez Wallgren.

“Our waiting list has now reached over 80,000 AEC professionals who want to access Finch. We are onboarding more and more leading global architecture firms who want to be part of the development but for all of those on the waiting list, who are Rhino / Revit users working with residential projects, we’re now inviting them to explore Finch Basic. Finch Basic includes all key figures and calculations in this generative solution to generate a proper mix and circulations, and customers can build their own plan library.”

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Finch Basic

Finch Basic costs €49 per month and is aimed at those looking to use AI to generate residential designs based on their specified mix, resulting in thousands of iterations meeting the apartment mix and circulation requirements. Users get auto-generated metrics: Gross Floor Area (GFA), Gross Internal Area (GIA), Net Internal Area (NIA), Usable Floor Area (UFA).

There is another tier, Finch Enterprise, aimed at larger firms focussed on residential who have their main workflow in Rhino, but this requires a more manual onboarding process, so is limited by Finch’s in-house resources and cannot be open to everyone.

Enterprise is also built for teams, as opposed to individuals, and will have all the graph rules which have been recently developed, and AI generated plans. Enterprise customers get to create shared custom plan libraries, furniture libraries, graph rules, and compliance checks.

The main feature in the Enterprise tier is that when generating plans, customers can build their own data sets, to generate results that adhere to local regulations and incorporate their practice’s style (design rules) in their Finch preferences – add custom objects, include accessibility bounds, lock constraints (like corridor / room width). Enterprise customers get two sets of results: one from the custom data set and generic Finch results. (see Enterprise demo video).

The process

Put simply, the architect creates massing in Rhino, Grasshopper or Revit (each mass will be interpreted as a building). Finch brings in that geometry (via a plugin). If the mass needs to be changed, it can seamlessly bring in those edits from the source conceptual tool.

Finch provides key metrics feedback to the designer: gross floor area and net internal area. It then slices up the building into different storey heights so the process of generating floor plates can happen. This is based on multiple scenarios – unit mix with stairwell variations, double corridors with stairs (US market), or cores connected to corridors (in development). Alternatively, you can generate around an existing corridor / core if you are doing a refurbishment. The user specifies the number of units to be generated per stairwell.

There are an array of side panel sliders with ‘weights’ which control the bias of the algorithm, daylight, area, grid lines, squareness. As the algorithm works you can see how well the unit mix fits the floor. Finch keeps iterating, and the longer you leave it, the more accurate it will get. This process is amazingly fast. All the time the user has control to impact the space designs which Finch outputs. Wallgren describes the Finch process as “a dance between generating and editing”, as the architect works with the Finch copilot. Once the floor plate is good, Finch displays all the different variations for unit mix that meet the criteria. Finch Basic can’t produce AI unit plans, so here users can assign a plan from their own library to be applied (watch this video).

Those on an Enterprise plan get AI created unit plans, including room load out (furniture etc.) and here Finch takes into account the façade and position of corridors, generating a proper architectural plan drawing, which can be streamed back to either Rhino or Revit, as a native Revit file.

Improved algorithms

As the software develops, the Finch team is constantly tweaking the algorithms and incorporating feedback from customers. The latest version of Generate Floor Plate allows architects to specify a range of stairwells, rather than specifically stating the number, allowing the algorithm to determine the most efficient configuration within these parameters. This flexibility extends to the distribution of units per stairwell.

Previous iterations of architectural AI tools often operated as black boxes, providing solutions without explaining their methodology. Finch now provides feedback when unit combinations prove incompatible with the building’s defined framework, such as oversized units or excessive stairwell numbers. This immediate feedback removes the need for trial and error.

The previous algorithm would solve within a margin of tolerance, so maybe not all units were exactly the area as specified. The new floorplate algorithm delivers exact dimensional accuracy. The new algorithms now also better cater to spatial constraints for building depth and dual-aspect ratios.

Beyond massing

Sometimes a project may already be past the massing stage before Finch gets introduced, as Nunez Wallgren explains, “We have been opening the pipeline allowing users to upload walls from Rhino, Revit, Grasshopper, corridor and the stairwells too, and then just generate the floor plans. We are opening up the cases where they can use Finch, depending on what stage the design is at.”

Wallgren adds, “The only thing you can be sure of when you talk to creative people, like architects, is that they don’t always necessarily want to follow a straight-line workflow. Being able to jump in and out of the process is very crucial to us, but also very hard when you’re building a product! The openness and customisability of the software is key.”

Artificial Intelligence (AI)

Finch uses a mixture of techniques to generate and analyse spaces. “Everything in our system is based on our Finch graph which is the logic of architecture,” explains Wallgren, “When we generate things, Finch doesn’t think it’s a good idea to go from the elevator into the toilet, into the bedroom. It’s more like understanding the composition of space, what makes sense, how we build architecture.

“These kinds of ‘soft’ problems are much more suitable for AI solutions, while, for example, when we generate a floor plate, when you want the core to be 1,400 mm, then a parametric and algorithmic approach is much better. But we are experimenting with other techniques as well. You can combine techniques, for example, playing chess on a computer. There are algorithms, there are rules, but you could also train the computer to play that game.”

The only thing you can be sure of when you talk to creative people, like architects, is that they don’t always necessarily want to follow a straight-line workflow. Being able to jump in and out of the process is very crucial to us, but also very hard when you’re building a product – Jesper Wallgren

Many firms are worried that AI software developers will steal their IP. With Finch giving design alternatives, Wallgren is keen to assuage any customer fears, “One thing that we’ve said now that has also been very important to our customers is that their plans are not part of the bigger model that we train. We collect a lot of data on built projects all over the world, to train our models, and then apply this to our customers’ results. But we’re not training on their data because that has been one hot potato!”

Conclusion

It’s great to see Finch finally getting out a release available for wider adoption, just for firms to see what is possible with algorithmic design in residential space planning. The advanced Enterprise features require a deeper onboarding, and obviously come at a higher cost, so access is limited but still worth talking to Finch about and registering your interest.

It’s interesting that speed really isn’t an issue for Finch; it’s being able to accommodate and understand users’ broad application areas. Finch needs not only deep space planning knowledge but also to be able to cater for an ever-increasing array of design variables. The Floor Plate V2 is a big improvement here and keeping the user updated on what’s happened is so much better than ‘computer says no’.

Finch will be joining us at NXT BLD and NXT DEV in London, 11-12 June 2025, along with all the best AEC software start-ups. Be sure to add the conference to your diary.

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Speckle began as a research project during Speckle founder and CEO Dimitrie Stefanescu’s PhD studies at University College London. It evolved into an ‘insider’ industry hack, with Speckle COO and cofounder Matteo Cominetti experimenting with the technology during his time at Foster + Partners. The goal was to find alternative methods for sharing, querying, and viewing BIM models -circumventing proprietary lock-ins, developer APIs, cumbersome ‘everything’ file transactions, and centralised file servers.

From its interoperability beginnings, a community grew, and Speckle eventually secured funding to establish itself as a stand-alone company to accelerate development.

Initially catering to a coding-savvy audience of AEC experts, hackathon enthusiasts, and BIM developers, Speckle has since evolved into a suite of tools and workflow capabilities which can be deployed to drive and automate bespoke project processes. This has helped make Speckle accessible to a much broader audience.

Connect

Speckle is built around the concept of connectors, applets that sit inside commonly used AEC applications that open-up their data to be streamed into and out of a centralised, open granular model (or Common Data Environment – CDE).

These connectors act as an industry wiring harness, bridging applications from different developers that don’t share APIs or struggle to write reliable common open data file formats.

Speckle supports plenty of formats: Revit, Rhino, Blender, Excel, Grasshopper, PowerBI, SketchUp, Dynamo, Navisworks, AutoCAD, Tekla, ArcGIS, Unreal, Unity, among others. If a connector isn’t available, those with the necessary skills can create their own. We understand Tesla wrote one for Dassault Systèmes Catia.

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Collab

The next component is the Speckle central data hub, which handles data, federated project data and teams. Speckle can be hosted in any region or country to meet customer preferences or for compliance requirements. Alternatively, Speckle can host it for you.

Model and project data from all disciplines are streamed in real time to a central project Speckle Workspace, where the model definition can be composed, with overlays, offering view manipulation, filters, comment / discussions, measure etc. Everything is done through a simple-to-use browser-based Speckle viewer, which can also be set to synchronise views between users during collaborative meetings (follow mode).

Team members can now be assigned varying levels of access, whether to entire projects or specific permissions within them. Powerful capabilities include realtime tracking of model changes, down to individual elements. Users can see which objects were removed, added, modified, or remain unchanged.

The new deployable Workspaces and Teams features mark the beginning of Speckle’s move toward offering turnkey project hosting solutions for a broader range of BIM firms – especially those without the in-house expertise to shape and craft a Speckle server workflow or Teams deployment.

This will bring Speckle into contention with relatively high-priced project management BIM tools and cloud hosting services. See later for the business model.

Automate

Speckle launched ‘Automate’ in beta last year (read this AEC Magazine article) which it describes as a CI/CD solution, offering Continuous Integration (CI) and Continuous Delivery (CD).

Automation loops and processes can be triggered whenever a model changes. For example, if an object in an architectural model is edited, Speckle Automate can automatically run clash detection with geometry from all disciplines in the background, perform quality assurance or code compliance checks, generate reports, or run analyses. Everything is fully customisable – it’s totally down to how each firm wants to architect the automation.

As Speckle can pretty much talk to any API, loops can cross application boundaries, integrating customers’ tech stacks to work as one using Python and .NET.

Over the past year, Speckle recognised that some automation routines were too complex for non-coders. In response, significant improvements have been made to the user interface, making it more accessible and intuitive for project teams. Additionally, Speckle now offers templates for common functions. It appears that Speckle Automate will soon leave beta and become a supported product.

The formulation of Workspaces, Teams and Automate, together with the established connectors and mode hub, has enabled the company to streamline its offerings.

Speckle has traditionally operated with what could be considered a “suicidal business model,” offering everything as open source. The company’s revenue primarily came from those who chose to pay for Speckle server hosting — yet, they were never required to do so.

With the attraction of venture capitalists and development money (Speckle recently raised $12.5m) the company is shifting towards a more sustainable business model. That said, even with this change, the prices we’ve seen for the capabilities on offer remain an absolute bargain.

There are still free options for individuals, open-source software, and customers can opt to host their own Speckle servers.

However, the Workspaces and Automation capabilities will come at a cost per user and are not ‘open source’. There will be three Workspace plans that differ in security options, starting at £12 per seat, per month, rising to £60 per seat, per month with SSO and data region of choice.

Once ‘Automation’ comes out of beta, there will be charges based on automation instances, although a certain amount of usage will be built into enterprise plans.

Conclusion

Speckle continues to support its community by maintaining a free point of entry, while also developing advanced tools that simplify deployment. This approach should appeal to a wider range of firms, especially those with limited coding knowledge in house —previously a potential barrier to entry.

This all goes a long way to make Speckle a modern software company with a turnkey product to sell. There’s still lots of flexibility as to how it’s wired into company and project workflows, but it will be liberating for any project to step outside the silos of their BIM 1.0 tool sets.

In many ways Speckle is a low-cost retrofit that will allow existing software tools to deliver next generation granular, multi-disciplinary workflows, without compromising long grafted in-house skills on mature software. At the same time, it frees project data from proprietary software locked behind shareholder-driven pricing models.

Speckle could well go from being the secret sauce of the BIM illuminati to becoming the champion silo slayer for all project fiefdoms. It’s just too useful for the industry to ignore.

Speckle Con: sharing solutions to real world problems

At the recent Speckle Con event in London, presentations were dominated by users showcasing the wide range of innovative ways in which Speckle has been deployed.

From refining internal processes and developing custom automations to augmenting BIM data with fabrication data, solving structural challenges, and creating new cloudbased applications, the event highlighted the versatility of the platform for solving real world problems. Attendees also demonstrated how they integrated AI into workflows, collaborated on road and rail civil projects, coordinated project teams, and embedded an opensource Life Cycle Assessment (LCA) capability across their practice.

Speakers came in from all around the world: RHDHV, Herzog & de Meuron, BaneDanmark, Perkins and Will, Ramboll and LINK Arkitektur, to name but a few. The presentations will be available online soon and we highly recommend watching them all.

Of particular note was Frederico Borello from Encode, who demonstrated how Speckle served as a powerful connector, bridging the gap between low level of detail architecture to high level of detail fabrication.

Also worthy of mention was Jordana da Castro Rosa and Adam Burnham of Perkins and Will, who used Speckle tech to develop tools that could possibly be commercially sold, all originating out of AEC hackathons.

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The defining CAD system of the 1980s was DOS-based AutoCAD and its proprietary DWG file format, which has dominated the market ever since. However, the secrets of the DWG file format are now common knowledge and there are tens of drawing tools which all speak the same interchangeable language of lines, circles, arcs, and text etc.

Several tools are owned by long-standing CAD software companies, including Hexagon (BricsCAD), Gräbert (Ares) and Dassault Systèmes (DraftSight).

DraftSight offers a lot more than basic 2D CAD functionality. It supports LISP APIs, point clouds, drawing compare, and shortcuts. The software comes in Professional,

Premium and Network (licence) versions. Premium includes a sheet set manager, PDF import and batch printing, advanced 2D tools with 3D modelling, meshing and 2D parametric constraints. The Network version allows enterprise deployment with simultaneous usage and built in compliance, enabling cost savings.

The latest release – DraftSight 2025 – provides a range of new and updated capabilities that cover all the drawing and output bases, such as PDF export settings, Batch and Print settings and a Lasso Selection. It offers both menu and ribbon bar interfaces simultaneously. Below are some of the other highlights.

Dimensioning: a new auto dimension feature makes complex dimensioning tasks simple with minimal input. In addition to manual dimensioning, DraftSight’s Smart Dimensioning tools figure out the best dimension type based on the entity selected.

Table management: Tabular information can now organise data better, automating formulas, adding consistent formatting, grips for manipulating tables, and support for breaks and block insertion.

File formats: A new STEP file import feature integrates externally created 3D models into 2D drawings. The IMPORTSTEP command can bring in complex mechanical parts. The new EXPORTDGN command lets users convert DWG drawings to Bentley Systems’ DGN format to aid those working in infrastructure.

Flatten: For those with drawings that have entities spread over the Z depth, the flatten command brings everything down to zero. This enables the easy clean-up of files which may have artifacts in 3D space.

Block management: The new Block Structure Palette helps designers see nested blocks and complex hierarchies more clearly (preview, isolate). The palette also organises design elements better and reduces time spent looking through complex block relationships.

Visual style options: The Visual Style Manager offers multiple viewing choices – wireframe and realistic rendering, conceptual and sketch appearances, X-ray visualisation. Using custom presentation styles, users can select how and which entities appear within a single block. There is also more visual control with a fill visibility for various entities including polylines, solids, traces, hatches, and gradients.

Conclusion

DraftSight 2025 provides practical workflow improvements with overall better performance on loading, views and stability with big drawings. There are also usable upgrades to file management, block structure control, and dimensioning systems, together with expanded file support with STEP (for MCAD models) and DGN export (useful for AEC).

As DS licenses its core technology from Gräbert, it also has access to Gräbert evolving auto drawing capabilities, which were demonstrated at NXT DEV.

In the next release of DraftSight, if not sooner, we imagine we will see some particularly useful assistance in batch autogenerating drawings from MCAD and BIM models, as DS turns its focus to additionally cater more for AEC users.

Why does AutoCAD still cost so much?

With software budgets being squeezed, many AEC firms are questioning why AutoCAD still costs so much — especially when it’s no longer cutting-edge technology.

At time of writing, AutoCAD costs £1,986 / year. Meanwhile, BricsCAD Pro (Mac or PC) is £484 / year, DraftSight Professional £249 / year, DraftSight Premium (Mac or PC) £499 / year, and Gräbert Ares Commander (web, mobile or desktop) £300 / year. Of course, there’s also the cut-down version – AutoCAD LT – which costs £486 per year. But AutoCAD LT has limited API, 3D, automation and collaboration capabilities.

On a pure like for like basis, at today’s prices it’s possible to get four seats of DWG equivalent drafting to one full AutoCAD seat. That even goes up to eight to one on yearly subscriptions. Some vendors also offer the design director’s favourite – network licensing – where users can share a pool of licences.

Of course, it’s important to point out that users of Autodesk’s Suite / Collection bundles for vertical markets deliver better value, where AutoCAD is one of many commonly used Autodesk industry tools (Revit, Navisworks, 3ds Max).

However, the cost of these bundles will be going up in the near future and there will an end to the 2 for 1 perpetual to subscription 8-year deal.

All of this is giving AEC firms plenty of food for thought, as they re-evaluate their software estates.

The post DraftSight 2025 appeared first on AEC Magazine.

In construction, it’s easy to get swept up in the buzz around emerging technologies like robots, drones, reality capture, XR, and AI. Yet, despite these advancements, significant inefficiencies remain in everyday workflows – particularly in how the industry manages and collaborates on documents and drawings.

While established project management platforms like Procore and Autodesk Construction Cloud (ACC) offer more sophisticated solutions, HP sees a gap in the market for a simpler, more cost-effective alternative. Enter HP Build Workspace, a new cloud-based platform developed by HP’s Construction Services Division in Barcelona, which works closely with the company’s DesignJet large-format printing team.

“We identified that there were a lot of people that just weren’t using those tools [Procore, ACC] precisely for those reasons [cost, complexity], and therefore there was an opportunity to really simplify the process,” explains Daniel Martínez, global head and general manager, HP large format.

HP Build Workspace aims to tackle a range of common pain points in construction, from managing and distributing drawings to documenting site visits, generating site reports, and converting legacy drawings into editable vector CAD files.

The team behind HP Build Workspace spent several months embedded at construction sites to better understand workflows and pinpoint areas for improvement. One key observation was the time-consuming and fragmented way site conditions and issues were documented and communicated, as Martinez explains, “[They are] basically taking photos on their phone, going back to their office, downloading the photos onto their desktop and sorting them out. They’re then spending hours preparing the reports.”

With HP Build Workspace, photos taken on-site can be immediately linked to specific locations on floorplans through an iOS or Android mobile app, significantly simplifying documentation. Observations can be categorised, augmented with text or voice notes and then automatically fed into reports that can be shared easily with other project members.

HP Build Workspace provides a centralised hub for document management, enabling teams to access files / drawings from anywhere. Everything is managed through the cloud platform, ensuring a single source of truth and providing an audit trail. In contrast to relying on isolated communications via WhatsApp or email, all stakeholders are directed to the platform via a link. In the future, HP Build Workspace will also be able to sync to cloud storage services including Google Drive, Dropbox and OneDrive.

A new life for legacy drawings

Perhaps one of the most innovative aspects of HP Build Workspace is its ability to convert legacy construction drawings into CAD-editable vector files with much higher accuracy than before.

“It’s a big pain point today,” explains Martinez, adding that most companies ship their PDF or scan files overseas, or hire drafters locally. “It’s a very expensive process, very time consuming,” he says.

“We scan millions of drawings a year, and [automatic conversion] is a service that our customers have been asking for, for years. We just hadn’t necessarily focused on it or felt that we had the right technology to address it the way that we felt that it should be addressed,” explains Martinez.

The technology that Martinez is referring to is, of course is AI, specifically machine learning (ML).

HP has been refining the AI behind this capability for over three years, using a combination of real-world customer data and synthetic files to train its models. The system applies a combination of AI models – some remove noise from the initial image, others separate different elements into layers.

“We have very high accuracy on certain types of CAD files,” says Martinez. “Imagine old archive drawings that have a lot of image noise in them, or are not very, very clear as you get them scanned, we can apply ML to get a higher level of accuracy than anything existing on the market today and the more people that use it, the more accurate it gets.”

The system can detect lines, polylines, arcs, and text. Once text has been extracted and indexed, users can search on that data. Outside of HP, there are several AI systems currently in development that enable firms to use Large Language Models (LLMs) to make sense of and recognise patterns within large sets of unstructured data. It’s hard to imagine that HP isn’t planning something similar with the data extracted from drawings, such as title blocks, notes and dimensions.

The conversion service comes with a simple editor. Here users can change lines that were incorrectly converted from dashed into solid, connect lines that should have been snapped together, as well as clean, remove or add elements. This isn’t just to improve the quality of individual documents – all this information gets fed back into the system to improve the AI. “The customer can define if it’s accurate enough for them, and we get real time feedback from that,” says Martinez.

Customers get to choose to opt-in or not, but as Martinez explains, HP only looks at the process. “The fact that you’re sharing the files for ML doesn’t mean that we have access to the content in any way, shape or form,” he says.

By tracking conversions, HP can understand what percentage of files have been accepted by the customer and, as new versions of the training model are released, if it’s improving or not. Martinez admits there have been cases when the success rate went down. “We’ve then been able to course-correct and eliminate whatever it was in the system that was affecting the quality of the output,” he says.

The big question is: will things ever get to a stage where the end user doesn’t have to check for accuracy? Martinez responds, “PDF files that were converting back into vector that have that vector layer information embedded? Yeah, we’re very close to 100%. If it’s a very old drawing that’s done by hand, the success rate is obviously much lower than if it’s a very clear line drawing that we can convert quite easily.

Physically connected to site

HP Build Workspace also integrates seamlessly with HP SitePrint, the three-wheeled robot that prints 2D plans directly onto construction site floors, with a view to replacing slow, error-prone manual layout processes (read this AEC Magazine article).

The aim is to enable general contractors, specialist contractors, and construction management firms to quickly and accurately set out the locations of building components. This streamlines site preparation, ensuring everything’s ready for the various trades to come in.

Since its launch in 2022 there have been several improvements to the technology, including the recent addition of a Revit plug that allows SitePrint-ready plans to be exported from the popular BIM authoring tool.

The new HP SitePrint Value Pack 3.0, announced this month, is said to deliver a 30% boost in print efficiency compared to its predecessor, which had already introduced similar performance enhancements earlier this year.

Most of these improvements are around navigation – moving from A to B – which is how the robot spends much of its time. Previously, it did this at 0.4 m/sec, but now it’s nearly doubled to 0.7 m/sec. Meanwhile, the print speed has seen a slight increase, from 0.33 m/sec to 0.35 m/sec.

HP Smart Navigation gives the robot a new integrated front-facing camera which creates a 3D representation of the robot’s surroundings, allowing it to detect unmapped obstacles on the job site and intelligently adjust its navigation route in real-time.

HP SitePrint Value Pack 3.0 also introduces shadowing, a new feature designed to prevent the robot from navigating into areas where it might lose line of sight with the robotic total station.

HP is also turning the robot printer into a device that can be used for reality capture. It is working with HP SitePrint customers on a proof-of-concept to check surface flatness, to help ensure surfaces are ready for construction. And it can do this while printing. For example, it can measure the flatness of a drywall / partition track, and then print notes in reference to the corrections that need to be done when installing on site.

The HP Reality Capture Technology Flatness Check will be sold as a service for HP SitePrint through subscription and is due to launch in 2025.

Conclusion

When HP Build Workspace was announced last week, it raised a few eyebrows. Does the AEC industry really need another collaboration platform, and will HP be stepping on the toes of established players?

The reality is that many AEC firms still rely on manual workflows, and these are the companies HP is targeting. The goal is to streamline and automate familiar processes like document distribution, site reporting, and vector conversion—bringing efficiency to areas where it’s often lacking.

That said, there are some gaps in the current offering. For instance, there are no built-in drawing markup tools, and while users can annotate plans with notes and site photos, it would be even better if these were automatically geolocated.

Of course, there’s significant potential for future enhancements. Right now, the platform focuses largely on 2D workflows, but could it evolve to support BIM workflows? Instead of just a camera, could it use a smartphone’s LiDAR sensor to capture site conditions as 3D meshes? And could reality capture with SitePrint extend to basic construction verification?

While some competitors offer more advanced features like these, it seems likely that HP will stick to simplicity. After all, many AEC firms are still wrestling with getting the fundamentals right, and HP Build Workspace might just be what they need to bridge that gap.

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At AEC Magazine, we’ve lost track of the countless ways software companies have altered their pricing and licensing models over the nearly 20 years we’ve covered BIM.

What’s evident is that this pace of change is accelerating as developers continue to refine their business models, shifting from traditional per-unit pricing to a ‘service-based’ model.

It now appears that if one major player successfully implements a change— measured by increased revenue or seats sold— the rest of the market will sheepishly follow.

This hasn’t helped customers. Design IT directors manage tech stacks which typically comprise multiple products, from multiple vendors, across multiple sites and possibly multiple geos.

Licence model changes are typically made to increase the revenue of software firms. This increases the cost of ownership and can also increase the time it takes to manage those licences. In short, it drains hard pressed budgets. Operating the same product, but on multiple different licences, increases the chance of being fined under licence compliance audits.

When a firm consistently adds new seats each year, the likelihood of differences in End User Licence Agreements (EULAs) increases, especially as software companies operate multi-year licensing but are rapidly evolving their licence models.

One might expect vendors are offering diverse licensing options to accommodate the wide variety of business needs, but subscription models in our industry remain surprisingly inflexible.

Business evolution

The design technology market is what one would call a mature software industry. In the 1980s, firms like Autodesk and VersaCAD pushed architects to trade in their drawing boards for desktop CAD. Today, it’s safe to say that professional design firms now rely on CAD systems far more than paper.

Over time, the opportunity for new sales has diminished, leading software firms to focus on getting existing customers to purchase more. In business parlance this means that the CAD market is highly saturated and highly penetrated. This saturation often results in diversification, with vendors developing additional products to expand their customer base. Their sales departments become very concerned about ‘attachment rates’.

Companies like Bentley Systems and Autodesk, once known for a single product, have now expanded to offer hundreds of solutions across various vertical markets.

Occasionally, a new generation of technology emerges, allowing companies to replace outdated systems. These shifts are rare, occurring roughly every 10 to 15 years.

Historically, such transitions have aligned with major operating system changes, like the shift from Unix to DOS or DOS to Windows. However, during these periods of transformation, it’s never certain that the dominant applications or leading software firms will retain their top position post-transition.

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Perpetual to subs

For about 30 years, software firms sold perpetual licences, granting users never ending access to a particular version of the design software. Depending on the development cycle, every few years the vendor would go back to try and upsell the customer to the next release by hopefully providing features deemed worthy of the upgrade price. This was always a hard slog for software firms and cost a lot in marketing and sales. Maintenance fees became common to naturally progress the sales cycle. Still, many customers would not upgrade every release, typically upgrading every three years. It was possible to be an Autodesk customer that hadn’t spent any money with Autodesk for years.

As software vendors diversified and created numerous applications for design management and creation, the opportunity for bundling emerged. Companies like Corel, with CorelDRAW, pioneered the idea—appealing to users’ desire for perceived value by offering multiple applications at a discounted rate. Autodesk followed suit in 2012, capitalising on vertical markets by bundling popular products like AutoCAD, Revit, and Navisworks.

In 2013 Adobe then championed subscription and moved its Creative Suite product delivery to the cloud. Subscription replaced perpetual licences and the cost of ownership per licence went up.

Pretty much all software firms learnt from Adobe’s experience. In the CAD space Autodesk was first to manage the migration.

In 2016, Autodesk introduced subscription and transferred Suites into Collections as an alternative to perpetual licences. By 2020 Autodesk wanted to stop perpetual sales and convert customers and gave customers a number of years to migrate. At the same time, it culled network licences and moved to named user sign on, mandating a seat per user.

While this was shocking, Autodesk did offer a killer deal, offering two subscription licences for every single perpetual licence handed in, for a period of 8 years. Depending on when firms moved, some will need to start paying for these extra licences from 2028 onwards (in four years’ time). It’s likely that the design IT manager who signed up for the deal, is no longer at the same company.

The last five years

Today, we have a world of connected cloud and mobile apps combined with named user subscriptions, giving vendors direct access to customer usage and contact details, which were previously obscured by reseller channels. This direct link also opened-up new possibilities for increasingly direct sales models, services and usage billing. Procore, for example, has championed ‘per project’ fees.

As software firms have further refined their cloud and subscription packages, many historical discounts have been removed.

In response, some customers have adjusted their strategies to fit their budgets, downsizing certain products and replacing applications from developers perceived to be price gouging. Of course, this approach only works when viable alternatives are available.

We’ve come across several instances where software vendors have raised prices by 100-300%, making it difficult for existing customers to avoid steep hikes or forced product migrations. Vendors often pressure clients by threatening to shut down hosted servers for ‘legacy’ software, forcing them to accept new terms or face repurchasing all software at full market price.

Design IT directors already juggle billable hours alongside IT management tasks such as upgrades, cross-grades, and user onboarding and offboarding. When vendors go rogue, the extra time needed for evaluation, transition, and migration to a replacement product becomes an unwelcome burden.

Cloud integration

The focus of several vendors has shifted to integrating and delivering services via SaaS. Procore, Autodesk, Hexagon, Trimble have all expanded and embellished the cloud component of their business. New features are increasingly being added, as opposed to delivered in the design software.

We’re moving toward a world where pure-play desktop applications are becoming rare, with users relying on vendors for hosting, applications, collaboration, and business functions. This is already producing some anxiety in customers who fear being trapped in proprietary cloud with limited API access. Perhaps sensing this distrust, most vendors are now talking about how ‘open’ they are, should that be file access, programming, or Application Programming Interface (API).

Artificial Intelligence

Although current AEC software features limited artificial intelligence, AI is poised to make a significant impact when applied at scale, potentially transforming the industry with advanced expert systems.

For the next year or so we will probably see small features and tasks benefiting from AI with more in-depth applications after that. AI-driven expert systems promise significant productivity benefits, posing a challenge to existing software business models. In 10 years’ time, one wonders how many seats of full BIM will be required to manually hand craft detailed schematic design models and generate documentation. With less software and more service, business models will change.

Conclusion

The need of software firms to maintain growth in a highly saturated and penetrated market has led to rapid ‘innovation’ in business models which outstrips the budgets and perceived value provided to customers. Design IT directors are having to juggle budgets to provide teams with the tools they need.

After years of feedback and complaints, it was a logical choice at this year’s NXT DEV conference to host a panel discussion on how software pricing, licensing, and business models affect firms (see box out below).

The frustration levels are high and with price negotiation seemingly being automated out of the process, there seems to be a valid discussion to be had over value. If a software tool is biased towards conceptual design, it might be heavily used for three months out of a three year project, but it’s priced as if it’s used eight hours per day, every week of every year.

At AEC Magazine, we’re already contemplating the future beyond individual software subscriptions. We’re beginning to see firms experiment with project value-based fees. With the advent of AI, auto-drawings, automation, and expert systems, the potential to significantly reduce the amount of software, labour, and time needed could drive productivity beyond anything we have seen before.

As the industry remains focused on recurring seat licence volumes, the future may demand a hybrid business model combining software access with transactional services and monitored CPU/GPU usage. This shift could necessitate software companies gaining deeper insights into project or customer finances—a prospect that is unlikely to go down too well.

The voice of the customer: NXT DEV panel discussion

After hearing numerous complaints from design IT directors about the constantly changing business models of software companies, we decided to dedicate a panel session to this topic at our recent NXT DEV conference. The goal was to offer critical feedback to current software and service providers in the AEC market, while also providing key insights to start-ups developing their pricing and licensing strategies.

The panel session was moderated by Richard Harpham, formerly of Revit, then Autodesk, and now co-founder of Skema. The panel included Iain Godwin, ICT Consultant to many AEC practices and former IT director / senior partner at Foster + Partners, Jens Majdal Kaarsholm, director of design technology at BIG (Bjarke Ingels Group), Alain Waha, CTO Buro Happold and Andy Watts, head of design technology at Grimshaw.

Many presentations at NXT DEV highlighted a growing concern among AEC firms about their data being locked in the cloud servers of software vendors, compounded by fears of restricted access through proprietary APIs. This pointed to a clear trust gap between vendors and their customers.

The panel members are responsible for their company’s design software estate, and explained how they are constantly evaluating value vs cost. They expressed how the felt ‘pushed into a corner as to how we will pay for technology’ by vendors.

Waha expressed concern about vendors engaging in ‘rent-seeking,’ aiming to extract money for shareholders without adding value. “They have identified us as sheep and we cannot defend against a large dominating organisation who will be rewarded and incentivised by capital at scale.” He then highlighted the irony that while these funds prioritise shareholder profits over technological advancements in the built environment, people, including himself, also benefit from strong pension returns.

Harpham played devil’s advocate. He said, “Vendors are not trying to do physical harm to the customers but there are business goals that make you change the way you work. You only have so many levers you can pull — you can ask a customer to pay more for what they have and right now that’s running about 5% per year. You can change the metrics and that ‘s what happened when we moved to subscription. You can re-package and that’s Suites/ Collections and then there’s licence compliance.”

Godwin, who was instrumental in the first Open Letter to Autodesk, stated that customers required trust in relationships with vendors. There were many aspects of the relationship with Autodesk that were schizophrenic. The Revit development team was trying to do its best, but the monetisation process and compliancy model undermines the trust and doesn’t help firms feel like they are getting value out of that relationship. And that was just the first five minutes!

We think this panel session is essential viewing. Tune in to hear what else was said.

NXTAEC.com

As a follow on to NXT BLD and NXT DEV 2024, our AEC technology conferences, we have launched NXTAEC.com, a dedicated video website where you can view all the talks from our recent events, including the incredibly honest Pricing, licensing and business models panel discussion.

NXTAEC.com is free. You just need to register. By implementing a registration system, we can offer capabilities like ‘watch later’, ratings, comments, playlists, share and dedicated video search with tags. Over time we plan to add more community features and facilitate ways to keep in touch with people you meet at NXT BLD and NXT DEV.

For now, we have uploaded content from the last three years of NXT BLD and the the last two years of NXT DEV. We will spend the Autumn backloading all the previous NXT BLD talks.

We want to keep the NXT BLD and NXT DEV vibe going throughout the year, so we also plan to use the site to produce and feature demonstrations from the really innovative AEC startups which we discover from our day job of researching the market for our bi-monthly AEC Magazine .

If you have not done so already, please register now.

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In a mature market, developing a new generation application involves playing a long game. Even if you are already the market leader, it’s hard to compete against your own, widely adopted products, because of customer inertia and legacy concerns.

So spare a thought for BIM 2.0 startups with far fewer revenues and much smaller customer bases, who face an uphill struggle but are still aiming to reinvent modern design software.

Among the firms striving to compete against Revit as a pure-play BIM platform are Arcol, Qonic and Snaptrude. with at least three more still in stealth mode and likely to emerge in 2025.

Arcol, Qonic and Snaptrude have entered the market with limited but carefully targeted feature sets, designed to be of immediate use in existing workflows. At first glance, it might appear as if they are aimed firmly at conceptual design. But make no mistake: all three have an eye on the long game. All three intend to become leading BIM platforms.

Modern computer languages, advances in web graphics and distributed cloud compute are bringing a new generation of tools to the market. When compared feature-by-feature to industry-leading, desktop-based BIM tools, these next generation tools may, at first, look quite limited. But the advantages of cloud delivery mean that new features can be streamed and added rapidly, giving incredible development velocity. Parity of features, depth of capability, and width for edge case designs could take just three to five more years of focused development.

The BIM 2.0 company with the most venture capital backing ($21.8 million) and the biggest development team is Snaptrude, headed up by CEO Altaf Ganihar. So far this year, Snaptrude’s BIM SaaS application has seen 26 releases, with another 16 planned before November 2024.

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The story so far

At AEC Magazine’s NXT DEV event, an industry figure who will go unnamed described Revit as “1970s thinking delivered in 1980s coding.” With many mature users demanding more updates and renewed software architecture, Autodesk CEO Andrew Anagnost stated there was to be no next generation of Revit, or in his words, “no faster horse”.

Instead, Anagnost presented the prospect of a cloud-based, data-centric tool called Forma. So far Autodesk has delivered a concept engine, which we believe will be fleshed out to become a cloud hub for what comes next in AEC at Autodesk. Meanwhile, Autodesk is busy architecting a data bridge between the Revit desktop and its Forma cloud back-end.

Snaptrude, meanwhile, has been developed to work and play well with Revit’s RVT file format and to find a niche in today’s BIM workflows. With its current feature set, it best fits workflows that involve rapid concept modelling and loading an RVT into the cloud for collaborative working with mark-up and editing capabilities.

Snaptrude is especially useful in space planning, but not as an end-to-end solution. For now, you would have to go back into Revit for coordination and documentation using the bidirectional link.

However, Snaptrude’s development is, by any measure, happening at high velocity. Ganihar compares his extensive development team to six internal startups, all working on different areas of the programme and delivering continually. Now that those developers have mastered the quality assurance that this parallel process demands, they can create a new release every week. And they do all this at the same time as supporting customers and using their feedback to drive the development cycle.

Mastering rapid development means that Snaptrude claims it will be able to deliver schematic design tools by the end of the year. This development may take most of next year to perfect, but the expansion enables Snaptrude to start work on developing different disciplines, such as structural and MEP capabilities.

The end goal for Snaptrude is big, Ganihar claims. “We want to be the OS for construction, which means using the same model to do clash detection, create the drawing, the quantity take-offs, costing take-offs, to produce the bid documents. We can actually do the full gamut, because we are not based on files. It’s a single database. And each one of these is just an instance of our database representation.”

But Snaptrude isn’t just an in-the-cloud Revit clone. The philosophy of the software is to drive productivity through automation of workflows, both micro and macro. As Ganihar states, “Next year, I think we’ll be very close to completing the schematic workflow. While we can replace like-for-like, we are also automating the design process. We are automating concept modelling, the visualisation and the drawing process.”

Growing portfolio

So far, Snaptrude’s customers have started pilots or used the software on live projects because of its promise to cut nonbillable hours. This is achieved by reducing the number of buttons that need to be pressed; the number of applications required; and the speed of output, whether the deliverable is an area model, a presentation, a render or a drawing. The target benefit that Ganihar cites most frequently is one-tenth of the time.

Snaptrude is also deploying AI. “The most successful feature we launched recently was area modelling. You can bring an area list from a spreadsheet programme and it automatically creates the blocks. Then you can automatically block and stack them, based on adjacencies, into a building footprint. This is done through physics-enabled AI, not the GPT kind. It’s logically solving the problem using daylight simulation, adjacencies, etcetera,” he says.

Snaptrude also has its own AI rendering technology, which utilises Nvidia graphics and Stable Diffusion, bypasses 2D-to-3D conversion, preserves a design’s geometry and is less likely to ‘hallucinate’. Drawings, however, is the most-often demanded feature. While Snaptrude is developing its own automated drawing capabilities such as auto-dimensioning, auto-tagging and auto-labels, the company has also licensed the DWG engine of Graebert, developer of Ares CAD, which is one of the most widely used DWG engines in the industry (as seen in DS DraftSight, Solidworks and Onshape).

Ares is designed for the cloud, desktop and mobile, which means Snaptrude can easily connect to it via API. The first stage will be a connection between a live link between Ares and Snaptrude. Graebert has also been working on autodrawing technology to accelerate drawing production. It looks like Snaptrude will be first to bring that to market in a BIM context both through its own internal work and through partnerships.

Ganihar sees this as a key technology to add and sees potential adoption in markets like Asia where Graebert Ares is popular, and AutoCAD and Revit LT are under market pressure. Snaptrude has managed to sign up Datech Solutions (part of TechData and distributor of Autodesk products) for distribution in Asia Pacific. Ganihar explained that there is great potential in cost-sensitive markets.

What’s next?

Snaptrude’s next big feature release should be live in October. It will support presentation drawings, instant renders and enhanced graphics. There have been improvements to real-time data for areas, costing and take-offs, as well as interoperability advances supporting Revit and Rhino, better geometry and BIM capabilities. This work connects the workflow from early RFPs to schematic designs.

Along with feature updates like coloured and monochrome massing, better snaps, drawing offset mode, select to move, offset and voids on masses, the Sketch-to-BIM capability has been enhanced to support Revit families and curtain walls.

In workspaces, imported Revit files will have families extracted and added to your team library with a single click. These can be managed from a single space. There will now be a command line (because CAD folks will never give this up!), but this will be AI-enhanced and more powerful.

Snaptrude is working towards a philosophy it calls ‘LOD hopping’, which means that, at any stage, the user can hop to a different LOD level to make design iterations, without having to worry about corrupting the model or downstream

In drawings, labelled drawings can now be created directly within Snaptrude, along with the ability to generate sheets in various sizes and scales and export them as PDFs.

In AI rendering, users will be able to create photorealistic renders and artistic graphics for their designs while respecting geometry, and soon, materials. The system is intelligent enough to understand BIM data, which Snaptrude plans to leverage in future releases to enhance quality.

There’s a new Rhino import capability, too, which uses a dedicated manager. Users can bring in geometry from Rhino, edit geometries currently supported inside Snaptrude and eventually take the detailed model to Revit for further documentation. Export of models to Rhino is performed through fbx or obj exports.

In parametrics, curtain walls and stacked wall parametrics are now supported. The new parametric wall graph will enable parametric editing in BIM mode for walls, floors, slabs in massing mode and on imported Revit projects. The graph will form the foundations to support other parametric elements in future releases. Snaptrude is working towards a philosophy it calls ‘LOD hopping’, which means that, at any stage, the user can hop to a different LOD level to make design iterations, without having to worry about corrupting the model or downstream.

Conclusion

With the industry looking to collectively move from desktop file-based design documentation BIM solutions to collaborative, cloud-based BIM databases, there is a lot at stake for the dominating industry players — Autodesk, Nemetschek, Trimble, Bentley Systems — especially with so many interesting start-ups that make their ultimate objective to replace existing seats.

Core BIM code is being rewritten. BIM formats are being granularised, collaboration is being built-in from the ground up and, in various ways, automation is going to play a big role in reducing the time spent doing donkey work.

While end goals may still be documentation and drawings, ways of getting there are going to be less distributed and more self-managing.

For Autodesk, it’s going to be especially interesting, as the Forma vision needs to be fleshed out and expanded beyond concept to indicate that the company is working on a broader development.

Every time Autodesk has addressed next-generation BIM, the company has acquired the technology (Softdesk = Architectural Desktop, Revit = Revit).

Autodesk purchased Spacemaker in 2020, which then became Forma.

But Spacemaker wasn’t a cloud BIM tool; it was for conceptual, early-stage design. To scale that up to being a cloud BIM tool will take time and resources. We will have to wait and see what’s shown at Autodesk University this year to rate Forma’s development velocity. But whatever happens, it’s clear that the competition – including Snaptrude – certainly isn’t hanging about.

Main image: Snaptrude is designed to play well with Revit

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