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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Snaptrude is working on enhanced interoperability between its web-based BIM authoring tool and Nemetschek Group BIM solutions, including Graphisoft Archicad, Allplan, and Vectorworks.

The aim is to enable architects to more easily transition between a range of BIM tools, harnessing the strengths of each tool at different project stages.

Interoperability with Nemetschek Group software will start with the ability to export Snaptrude projects into Archicad, ‘preserving all the parametric properties’ of BIM elements.

Project teams on Snaptrude have shared workspaces that also include a centrally managed library of standard doors, windows, and staircases. Upon import, Snaptrude objects will be automatically converted into editable families in Archicad.

In the future, the integration extend to a bi-directional link between Snaptrude and Archicad for synchronisation of model data and changes. According to Snaptrude, this will further enhance collaboration and efficiency in the design process, as users will be able to switch back and forth between the programs.

Snaptrude already offers bi-directional support for Autodesk Revit (a workflow that is explored in this AEC Magazine article).

“We want architects and designers to use the best tools for their needs without any hassles,” said Altaf, Founder at Snaptrude. “Snaptrude supports bi-directional interoperability with several BIM tools and is extending this capability to Nemetschek Group BIM design solutions. This is a move towards enhancing the way architects and designers work by incorporating industry-leading tools seamlessly into the workflow.”

Snaptrude is a web-based 3D BIM tool designed for real-time, multi-user collaboration. The software recently added an AI renderer to its feature set. According to the developers, the AI renderer recognises the geometry of models, understands scale, and is trained to understand context, foreground, background and material, so users have control over their renders.

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Written by Aaron Perry, Head of Digital Design at Allford Hall Monaghan Morris, and Andy Watts, director of design technology at Grimshaw

This must read report details what the AEC industry wants from future design tools, covering everything from data framework, context and scale, responsible design, and modular construction, to user experience, modelling capabilities, automation, intelligence, deliverables and more.

Watch the NXT DEV presentations from Aaron Perry and Andy Watts

NXT DEV 2023 – watch the video on NXTAEC.com

Aaron Perry, talking on behalf of a collective of medium-to-large AEC firms, gives a masterful presentation as he introduces the ‘Future Design Software Specification’.

NXT DEV 2024 – watch the video on NXTAEC.com

Andy Watts gives an important update on the specification, then hands over to Allister Lewis, ADDD, to talk about benchmarking software against the specification.

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In Buro Happold’s structural engineering team, we’re constantly working on unique and challenging projects, from towering skyscrapers to expansive stadiums, intricate museums to impressive bridges.

Our approach is all about exploring multiple options, conducting detailed analyses, and generating 3D and BIM models to bring these projects to life. But this process comes with the major challenge of interoperability – the ability of different systems to exchange information.

Since we collaborate with multiple disciplines and design teams from all over the world, we regularly deal with data from various sources and formats, which can be a real challenge to manage.

The AEC industry often deals with this by creating ad-hoc tools as and when the need arises (such as complex spreadsheets or macros). But these tools often end up being one-offs, used by only a small group so we end up reinventing the wheel again and again.

This is where the BHoM (Buildings and Habitats object Model) comes into play, a powerful open-source collaborative computational development project for the built environment supported by Buro Happold.

BHoM helps improve collaboration, foster standardisation and develop advanced computational workflows. Thanks to its central common language, it makes it possible to interoperate between many different programs.

Instead of creating translators between every possible combination of software applications, we just need to write one single translator between BHoM and a target software, to then connect to all the others.

The solution: The BHoM

The BHoM consists of a collection of schemas, functionalities and conversions with the following three main characteristics:

• It attempts to unify the “shape” of the data

• It is crafted as software-agnostic

• It is open source so that everyone can contribute and use it

Currently, the BHoM has over 1,200 object models with an extendable data dictionary and adapters to over 30 different software packages.

With the BHoM, we’ve refined and enhanced our approach to structural design.

Once the architectural model is received, using the BHoM we can quickly and precisely build several Finite Element Analysis (FEA) structural models for conducting structural analyses.

It’s possible to clean and rationalise the original geometries for specific purposes and assign/update attributes to all objects based on the results of both design and coordination with other disciplines.

Finally, the BIM model of the structure can be generated in an algorithmic manner.

BHoM in practice

It’s often thought that computational and parametric design is only applicable to the very early stage of a project that relies on very complex geometry.

The reality is, computational design is greatly beneficial at every stage: from the conceptual feasibility study to the detailed design of steel connections.

At Buro Happold, we use the BHoM to help us address multiple stages throughout a project, as demonstrated in the following case study examples which focus on the re-development of a desalination plant in Saudi Arabia into a huge museum.

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Modelling the existing and the new

Let’s see how a computational workflow applies to the modelling and analysis of existing structures making use of the BHoM.

For the Saudi Arabian project, all we had was a set of scanned PDF drawings of the existing structures.

Within a couple of months, we had to build accurate Finite Element Models for each of them and run several feasibility studies against the new proposed loadings.

A parametric approach was vital. Therefore, we developed a computational workflow that allowed us to create the geometric models of all the built assets in Rhino via Grasshopper by tracing the PDF drawings, assigning them with metadata and pushing them via BHoM into Robot to carry out preliminary analyses and design checks.

Of course, there’s no need to mention how much time and effort this approach has saved us compared to a more traditional workflow.

Moving on to the next stage of the project, we needed to test very quickly many different options for the proposed structures, by modifying grids, floor heights, beams and column arrangements, as well as playing with the geometry of arched trusses and trussed mega-portals.

Again, going for a computational approach was the only way to face the challenge and we developed a large-scale algorithm in Grasshopper.

By pulling data from a live database in Excel and making use of an in-house library of clusters and textual scripts, this algorithm was able to leverage the capabilities of the BHoM to model the building parametrically in Rhino, push it to Robot for the FEA and finally generate the BIM model in Revit – all in a single parametric workflow.

Managing data flow: BIM – FEA

As we move into later stages of the project, the more we can see how computational workflows are not only beneficial for geometry generation but also for data management and design calculations.

At Stage 03 and 04 we needed to be able to transfer and modify very quickly all the huge sets of metadata assigned to any asset within our BIM models while being able to test them on a design perspective in Finite Element Software.

Again, we developed an algorithm in Grasshopper leveraging the BHoM to allow for this circular data flow from BIM to analysis software – Revit and ETABS in this instance.

This made it possible to test and update all our models quickly and precisely, notwithstanding the sheer amount of data involved.

Interdisciplinary coordination

As usual, when moving forward in the project, coordination with MEP engineers starts to ramp up and when structures are big and complex, it becomes even more difficult. The challenge we had to face was intimidating. We had eight concrete cores, 45m tall, more than 9,000 Mechanical, Electrical and Plumbing (MEP) assets for the building and around 1,500 builderswork openings to be provided in the core walls to allow them to pass through.

On top of this, we had the need to specify openings of different sizes depending on different requirements based on the type of MEP asset, as well as the need to group and cluster openings based on their relative distance and other design criteria.

Again, a high level of complexity and a huge amount of data to deal with. Indeed, a computational approach was needed.

Using Grasshopper, BHoM and Rhino. Inside Revit, we developed an algorithm, graphically represented below.

Through grouping operations, model laundry algorithms and the parametric modelling of the builderswork openings, we were able to generate parametrically the BIM model of the cores provided with the required builderswork penetrations.

In parallel with this, the algorithm also generated the corresponding FE model of the core walls, so the structural feasibility of the penetrations could be checked before incorporating them in Revit.

The algorithm detected the intersections between pipes and walls, then generated openings around each intersection of different size and colour depending on different input criteria. Then, using a fine-tuned grouping algorithm, it clustered and rationalised them into bigger openings, wrapping all of them together based on user-input criteria.

Finally, after testing the openings in the Finite Element software, the algorithm pushed them into Revit as Wall Hosted Families and a live connection between the Rhino and the Revit environment streamlined any update process in parallel.

Producing large data sets

Moving even further into detailed design, the amount of data to deal with on a project of such scale becomes more and more overwhelming.

This is what we had to face when dealing with the design of the connections. Although the design was subcontracted to another office, we faced the challenge of providing all the connection design forces in a consistent and comprehensive format, both in textual and graphical contexts.

Indeed, this is not an easy task, especially when dealing with around 35,000 connections, 60 load combinations, 2,000 different frame inclinations, six design forces per connection and spanning over three different finite element software packages (ETABS, Robot, and Oasys GSA).

We had to deal with 12.6 million pieces of data and we had to do it very quickly, being able to update them on the fly. Again, a computational workflow was required.

Via Grasshopper and the BHoM, we developed an algorithm to extract, post-process and format the connection forces from the Finite Element models of all the assets of the project, serialise them in JSON, save them in properly formatted Excel files and show them graphically in corresponding Rhino 3D models via tagging and attributes assignment.

All this information was sent out for the design to be carried out by other parties.

Conclusions

Applying a specialised approach, relying on algorithmic methodology and leveraging state-of-the art computational tools, such as the BHoM, enable us, at Buro Happold, to deliver comprehensive and advanced structural solutions, ensuring efficiency, sustainability, and optimal performance across all the stages of the project.

Resources

[1] BHoM Documentation (2024)

[2] LOMBARDI, Alessio, (2023), Interoperability Challenges. Exploring Trends, Patterns, Practices and Possible Futures for Enhanced Collaboration and Efficiency in the AEC Industry, in, London, UK.

[3] ELSHANI, Diellza, STAAB, Steffen, WORTMANN, Thomas (2022), Towards Better Co-Design with Disciplinary Ontologies: Review and Evaluation of Data Interoperability in the AEC Industry, in LDAC 2022: 10th Linked Data in Architecture and Construction Workshop, Hersonissos, Greece.

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Autodesk has announced a partnership with SrinSoft to improve interoperability across a range of Autodesk and third-party CAD and BIM software tools. Through the agreement users can share, via ‘seamless cloud-based data transfer’ in Autodesk Construction Cloud (ACC), entire files or subsets of models.

At the heart of the partnership is BIMDeX, SrinSoft’s proprietary AI-powered interoperability platform, which has been integrated with Autodesk Data Exchange (DX) and Autodesk Construction Cloud (ACC) using Autodesk Platform Services (APS).

BIMDex supports a range of AEC, manufacturing and process plant software, including Autodesk Revit, Autodesk Plant 3D, Autodesk Civil 3D, AutoCAD MEP, Autodesk Inventor, DS Solidworks, PTC Creo, Tekla Structure, Autodesk Docs, and Microsoft Power BI.

Utilizing the proprietary BXF file format, BIMDeX supports data exchange across local file systems, offline workflows, and private clouds.

Through the collaboration customers can use BIMDeX connectors to share subsets of their model (geometry and properties) via ACC through a Data Exchange. According to Autodesk, this exchange can be permission-controlled, viewed, and bridged across hubs, making design data accessible through APS APIs.

The data exchange can be updated, versioned, and integrated into countless automated workflows triggered by events. Additionally, customers can create visually rich dashboards using Autodesk Data Connector for Power BI.

“Customers are demanding that the industry move beyond file sharing workflows, so that granular data can flow between apps and organisations, securely. When Autodesk launched Data Exchange and the toolkits to create connectors, we anticipated the need for hundreds if not thousands more connectors to meet that need,” said Shelly Mujtaba, Autodesk VP, product data platform.

“Now, SrinSoft’s interoperability business, BIMDeX, is able to bring their portfolio of connectors to Autodesk’s platform – and to many more customers. We are proud to work with SrinSoft to broaden the scope of their business through the Autodesk platform.”

The solution is built on BIMDeX’s AI technology for advanced geometry recognition, which is designed to enhance the platform’s ability to predict and resolve complex design conflicts, automate repetitive tasks, and offer intelligent insights based on design data.

Watch the video below to see the workflow between key apps including Autodesk Revit, Autodesk Plant 3D, Tekla Structures and Power BI.

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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.

The post Speckle matures appeared first on AEC Magazine.

Established in 2005, Dalux is a Danish software firm which has created a digital platform for almost everything outside of BIM authoring tools. It focusses on information management, design management, model validation, tendering, site inspections, and snagging, for construction firms, developers and consultants. Dalux’s software expands through the lifecycle to data handover and facilities management. The company is also scaling up into infrastructure and GIS.

Dalux started off creating what it claims to be the fastest BIM model viewing tool, being first to apply games technology to BIM geometry, an early entry into what is now the Common Data Environment (CDE) market. From that initial product Dalux has built a whole platform around its centralised data model, expanding to mobile and augmented reality.

Dalux now has a global user base of over 1 million professionals across 147 countries. Despite its scope and reach, the company is very much headquartered in Copenhagen, Denmark, which is the centre of operations and development.

The company has an annual user meeting, the Dalux Summit, which is hosted in Copenhagen. This year AEC Magazine attended to delve deeper into the products and the community. With over 1,800 attendees, the scale was much larger than we anticipated and the whole vibe was a unique experience.

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Dalux feels like a family business and the dialogue and interactions between customers and the team gave the distinct impression that development of features and capabilities was a much more interactive process than at other software companies. Dalux has ‘Hygge’, a Danish word that roughly translates to ‘cosiness.’

The family business is run by two brothers, Torben and Bent Dalgaard. Torben is the CEO and Bent is the CTO. In their morning address to attendees, one slide caught the zeitgeist perfectly – the brothers reassured the audience that Dalux is an independent software firm, that has no loans, no investors and is owned by Bent & Torben.

While many 19-year old firms that have been growing 60% annually for almost a decade would be wafting share value, revenue or profit as an essential part of their mainstage moment, they opted to reassure customers that, unlike firms with shareholders that are repeat plunderers of their customers’ design technology budgets, Dalux is not in that game. There are very few AEC software companies with this attitude that come to mind – the most notable others being McNeel (Rhino) and Qonic.

The Dalux product family

At the moment, Dalux offers nine products, which it has grouped in information management, onsite management and facility management, with almost half of its brands in on-site management.

BIM Viewer is free and works on desktop and mobile. It supports native BIM, IFC and drawings, with a range of free plug-ins for Revit, Solibri, Archicad, Navisworks and Tekla. It offers a suite of tools including measure, filter, properties, and make sections. Comments can be added, clashes from Solibri and Navisworks can be imported. We suspect that this is the gateway drug to the Dalux ecosystem!

Box is the core collaboration and CDE platform that delivers BIM geometry and data to collaborating project teams. It is accessed via the web browsers of supported mobile devices (iOS or Android).

Having extracted the data from the BIM authoring tool, Box centralises all the project information in managed folders for design and construction teams to view, review and approve 2D and 3D data with individual team controls. Additionally, Box offers the ‘always requested’ clash detection, for both hard and soft clashes, as well as perform other geometry checks, such as point clouds from as-built.

Dalux Box Sync will download folders and files between the web and a local computer. It will also upload any files you want or have changed, making them available to other project participants.

Field is the product for quality control, health and safety, snagging/punch list and on-site reality capture. It brings the latest drawings to site and assists in scheduling and managing site inspections with customisable checklists. While onsite observation/ snags, health and safety reports can be quickly created and documented with the phone’s camera, the system is smart enough to know where in the site you are located – time and floor. There are workflow tools to trigger actions to those who need to resolve remedial work. The reports are accessible to project workers and issues clearly identified on the latest drawings.

Field Basic is a free punch list tool that supports drawings and BIM models and enables tasks, collaboration amongst defined groups, and sign-off.

Field Sitewalk enables the quick capture of a site using video from a helmet-mounted 360 degree camera. The video frames make photographing the site effortless. These are automatically mapped in the Dalux system. Teams back in the office can use the system to see the current state of construction and even compare the site against the BIM model to see if the work is on track. The system offers some very clever registration between the rooms captured and generating the same view from the BIM geometry.

Infrafield is Dalux spreading its wings into the world of projects that span tens of kilometres, rather than metres with individual buildings. Given Dalux’s client list, we can well understand how Infrastructure became inevitable.

Infrafield required a new modelling engine technology to provide the expansive co-ordinate system. It supports 2D and 3D, Google Maps 3D tiles, drawings, GIS layers, terrain layers, and point clouds. Like ‘Field’ it can be used to track progress and capture issues. Users can create sections and cuts, measurements. It is seamlessly integrated into the Dalux ecosystem, so infrastructure models can be shared.

FM – facilities management – is probably another no brainer for following the design and construction data, into operations. It’s quite refreshing to not have to deal with the branding bludgeon that is digital twin. FM is a web and mobile content management system for 2D and 3D asset management, operations and maintenance. It combines floorplans, mapping and modelling based on location, aiding navigation. It offers a helpdesk ticketing system, work order generation, maintenance schedule and is a conduit for additional digitised documents, asset information, photos etc.

Again, the smart application uses GPS to position the user in floorplans and can be used in conjunction with QR codes for asset tagging or room tagging. The system comes with workflow tools to route tickets to the right department or person.

Handover is the Dalux product for packaging up and handing over design, construction and associated project information post build. Using templates, Handover can save a lot of time making sure the right information is used for FM downstream. It can output PDF reports and COBie files.

Tender is the secure app for distributing tenders on projects through Dalux and integrates to Dalux Field. Tender bids come with ready packaged up documents in a logical folder structure. The project owner remains in control and Dalux provides a full audit trail of any changes.

Conclusion

While US giants Procore and Autodesk Construction Cloud look to dominate the flow of data among construction and subcontractor firms, Dalux appears to be a European equivalent that is holding its own. However, the Dalgaard brothers have managed to keep the firm accessible to its customers and build a unique relationship.

As I understand, firms pay fees based on project size, as opposed to by number of users, meaning Dalux becomes the single source of truth for the construction data for all participants.

Dalux appears very support-centric, and it prioritises ongoing connection with developers and product champions in their customer base. It’s another reason why 1,800 people would visit Copenhagen to meet up with what felt more like a bespoke outsourced software developer, than a firm trying to meet next quarter’s targets.

Main image: In their morning address to attendees the Dalgaard brothers caught the zeitgeist perfectly

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Cintoo has launched Cintoo Metaverse, a new product portfolio designed to bring high fidelity reality capture data to an immersive environment.

The Cintoo VR Experience app is one of two initial apps in the Cintoo Metaverse portfolio. The VR app, which runs on Unreal Engine and is cloud-connected to the Cintoo platform, is designed to extend Cintoo’s collaboration and decision-making capabilities.

It allows project managers, engineers and installers to navigate reality models at a true-to-life 1:1 scale on ‘almost any’ VR device, as well as compare as-builts to as-designed by overlaying scans with 3D models.

3D scans and 3D models are all streamed from the Cintoo Cloud in real time, at the same high mesh resolution as the source point cloud thanks to Cintoo’s TurboMesh engine. According to Cintoo, no preparation work or pre-production is required.

To navigate around the reality model, the Cintoo VR Experience is using a technology first introduced to its platform earlier this year.

With the ‘teleportation camera’ users can teleport anywhere in the scene simply by pointing and clicking or navigating between scan set up locations.

In VR, users can create annotations, take measurements and then sync everything back to the Cintoo project.

Issues identified in VR can be exported in BCF Format, or synced with BIM Track, Autodesk BIM 360 or Procore.

“This is not just about visualization; it’s about driving actionable insights, reducing costs, and improving operations,” said Dominique Pouliquen, CEO of Cintoo. “Whether a construction, oil and gas or manufacturing company, the industrial metaverse enables you to harness your data in real-time, creating smarter, more efficient workflows.”

The second Cintoo Metaverse app, 3D Layout Experience, has been developed with Cintoo’s partner, Theorem Solutions. It allows users to navigate a 3D mesh, check clearances when moving equipment, and simulate future workspaces.

Meanwhile, Cintoo has closed a €37 million Series B funding round led by Partech, a global tech investment firm. With the fresh funding, Cintoo will enhance its SaaS platform by expanding its portfolio of integrations and will build on its new industrial metaverse experience and automatic asset tagging capabilities.

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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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The Autodesk AI brand debuted in Las Vegas last year at Autodesk University, but the launch lacked any real substance. Despite a flashy logo there were no significant new AI capabilities to back it up. The event seemed more like a signal of Autodesk’s intent to add greater focus on AI in the future — building on its past achievements. It came at a time where ‘AI-anything’ was increasing share valuations of listed companies.

Fast forward 12 months and at Autodesk University 2024 in San Diego the company delivered more clarity on its evolving AI strategy — on stage and behind the scenes in press briefings. Autodesk also introduced a sprinkling of new AI features with many focused on modelling productivity, signalling that progress is being made. However, most of these were for manufacturing with little to excite customers in Architecture, Engineering and Construction (AEC), other than what had already been announced for Forma.

In his keynote, CEO Andrew Anagnost took a cautious tone, warning that it’s still early days for AI despite the growing hype from the broader tech industry.

Anagnost set the scene for the future. “We’re looking at how you work. We’re finding the bottlenecks. We’re getting the right data flowing to the right places, so that you can see past the hype to where there’s hope, so that you can see productivity rather than promises, so that you can see AI that solves the practical, the simple, and dare I even say, the boring things that get in your way and hold back you and your team’s productivity.”

One of those ‘boring things’ is sketch constraints, which govern a sketch’s shape and geometric properties in parametric 3D CAD software like Autodesk Fusion, which is used for product design and manufacturing.

Fusion’s new AI-powered sketch auto-constrain feature streamlines this process by analysing sketches to detect intended spatial relationships between aspects of the design.

Automatically constraining sketches is just the starting point in Autodesk’s broader vision to use AI to optimise and automate 3D modelling workflows. As Anagnost indicated, the company is exploring how AI models can be taught to understand deeper elements of 3D models, including features, constraints, and joints.

At AU, no reference was made to similar modelling productivity tools being developed for Autodesk’s AEC products, including Forma. However, Amy Bunszel, executive VP, AEC at Autodesk, told AEC Magazine that the AEC team will learn from what happens in Fusion.

Another ‘boring’ task ripe for automation is the production of drawings. This labour-intensive process is currently a hot topic across the CAD sector (read this AEC Magazine article).

This capability is also coming first to Autodesk’s product design and manufacturing product. With Drawing Automation for Fusion, Autodesk is using AI to automate the process, down to the precise placement of annotations.

With the click of a button, the AI examines 3D models and does the time-consuming work of generating the 2D drawings and dimensions required to manufacture parts. The technology has evolved since its initial release earlier this year and now accelerates and streamlines this process even more by laying out drawing sheets for each component in a model and applying a style. Early next year, the technology will be able to recognise standard components like fasteners, remove them from drawing sets, and automatically add them to the bill of materials for purchase.

Once again, this feature will first appear in Fusion, but sources have confirmed plans to extend automated drawing capabilities to Revit—a significant development given the BIM tool’s widespread use for documentation. There’s also potential for autonomous drawings in Forma, although Forma would first need the ability to generate drawings. During the AU press conference, CEO Andrew Anagnost hinted that drawing capabilities might be in Forma’s future, which, if realised, could potentally impact how much customers rely on Revit as a documentation tool in the long term.

Both of Autodesk’s new AI-powered features are designed to automate complex, repetitive, and error-prone processes, significantly reducing the time that skilled designers spend on manual tasks. This allows them to focus on more critical, high-value activities. But, as Anagnost explained, Autodesk is also exploring how AI can be used to fundamentally change the way people work.

One approach is to enhance the creative process and Form Explorer is a new automotive-focused generative AI tool for Autodesk Alias, designed to bridge the gap between 2D ideation and traditional 3D design. It learns from a company’s historical 3D designs, then applies that unique styling language.

Lessons learned from Form Explorer are also helping Autodesk augment and accelerate creativity in other areas of conceptual design.

Project Bernini is an experimental proof-of-concept research project that uses generative AI to quickly generate 3D models from a variety of inputs including a single 2D image, multiple images showing different views of an object, point clouds, voxels, and text. The generated models are designed to be ‘functionally correct’, so a pitcher, for example, will be empty inside. As the emphasis is on the geometry, Bernini does not apply colours and textures to the model.

Project Bernini is not designed to replace manual 3D modelling. “Bernini is the thing that helps you get to that first stage really quickly,” said Mike Haley, senior VP of research at Autodesk. “Nobody likes the blank canvas.”

Project Bernini is industry agnostic and is being used to explore practical applications for manufacturing, AEC and media and entertainment. At AU the emphasis was on manufacturing, however, where one of the ultimate aims is to learn how to produce precise geometry that can be converted into editable geometry in Fusion.

However, there’s a long way to go before this is a practical reality. There is currently no established workflow, plus Bernini has been trained on a limited set of licensed public data that cannot be used commercially.

AI for AEC

Autodesk is also working on several AI technologies specific to AEC. Nicolas Mangon, VP, AEC industry strategy at Autodesk, gave a brief glimpse of an outcome-based BIM research project which he described as Project Bernini for AECO.

He showed how AI could be used to help design buildings made from panellised wood systems, by training it on past BIM projects stored in Autodesk Docs. “[It] will leverage knowledge graphs to build a dataset of patterns of relationship between compatible building components, which we then use to develop an auto complete system that predicts new component configurations based on what it learned from past projects,” he said.

Mangon showed how the system suggests multiple options to complete the model driven by outcomes such as construction costs, fabrication time and carbon footprint. This, he said, ensures that when the system proposes the best options, the results are not only constructible, but also align with sustainability, time and cost targets.

Another AEC focused AI tool, currently in beta, is Embodied Carbon Analysis in Autodesk Forma, which is designed to give rapid site-specific environmental design insights. “It lets you quickly see the embodied carbon impact at the earliest conceptual design phase, giving you the power to make changes when the cost is low,” said Bunszel.

The software uses EHDD’s C.Scale API which applies machine learning models based on real data from thousands of buildings. The technology helps designers balance trade-offs between embodied carbon, sun access, sellable area, and outdoor comfort etc.

Embodied Carbon Analysis in Autodesk Forma follows other AI-powered features within the software. With ‘Rapid Noise Analysis’ and ‘Rapid Wind Analysis’, for example, Forma uses machine learning to predict ground noise and wind conditions in real time.

Autodesk AI is also providing insights in hydraulic modelling through Autodesk InfoDrainage, as Bunszel explained, “You can place a pond or swale on your site and quickly see the impact on overland flows and the surrounding flood map.”

Simple AI

Autodesk is also diving into the world of general purpose AI through the application of Large Language Models (LLMs). With Autodesk Assistant, customers can use natural language to ask questions about products and workflows.

Autodesk Assistant has been available on Autodesk’s website for some time and is now being rolled out gradually inside Autodesk products.

“The important thing about the system, is it’s going to be context-aware, so it’s understanding what you’re working on, what project you’re on, what data you’ve run, maybe what you’ve done before, where you are within your project, that kind of thing,” said Haley.

With the beta release of Autodesk Assistant in Autodesk Construction Cloud, for example, users can explore their specification documents through natural language queries, as Bunszel explained, “You can ask the assistant using normal everyday language to answer questions, generate lists or create project updates,” she said, adding that it gives you access to intuitive details from your specifications that usually require lots of clicking or page turning or highlighting to find.

Getting connected

Like most software developers Autodesk is harnessing the power of LLMs or vision models, such as ChatGPT and Gemini. “We can use them, we can adapt them, we can fine tune them to our customers’ data and workflows,” said Haley, citing the example of Autodesk Assistant.

But, as Haley explained, language and vision models don’t have any sense of the physical world, so Autodesk is focusing much of its research on developing a family of foundation models that will eventually deliver CAD geometry with ‘high accuracy and precision’.

Autodesk’s foundation models are being trained to understand geometry, shape, form, materials, as well as how things are coupled together and how things are assembled.

“Then you also get into the physical reasoning,” added Haley. “How does something behave? How does it move? What’s the mechanics of it? How does a fluid flow over the surface? What’s the electromechanical properties of something?”

According to Anagnost, the ultimate goal for Autodesk is to get all these foundation models talking together, but until this happens, you can’t change the paradigm.

“Bernini will understand the sketch to create the initial geometry, but another model might understand how to turn that geometry into a 3D model that actually can be evolved and changed in the future,” he said. “One might bring modelling intelligence to the table, one might bring shape intelligence to the table, and one might be sketch driven, the other one might be sketch aware.”

To provide some context for AEC, Autodesk CTO Raji Arasu said, “In the future, these models can even help you generate multiple levels of detail of a building.”

AI model training

Model training is a fundamental part of AI, and Anagnost made the point that data must be separated from methods, “You have to teach the computer to speak a certain language,” he said. “We’re creating training methods that understand 3D geometry in a deep way. Those training methods are data independent.”

With Project Bernini Autodesk is licensing public data to essentially create a prototype for the future. “We use the licence data to show people what’s possible,” said Anagnost.

For Bernini, Autodesk claims to have used the largest set of 3D training data ever assembled, comprising 10 million examples, but the generated forms that were demonstrated — a vase, a chair, a spoon, a shoe, and a pair of glasses — were still primitive. As Tonya Custis, senior director AI Research, admitted there simply isn’t enough 3D data anywhere to build the scale of model required, highlighting that the really good large language and image models are trained on the entire internet.

“It’s very hard to get data at scale that very explicitly ties inputs to outputs,” she said. “If you have a billion cat pictures on the internet that’s pretty easy to get that data.”

The billion-dollar question is where will Autodesk get its training data from? At AU last year, several customers expressed concern about how their data might be used by Autodesk for AI training.

This was a hot topic again this year and in the press conference Anagnost provided more clarity. He told journalists that for a generative AI technology like Bernini, where there’s a real possibility it could impact on intellectual property, customers will need to opt in.

But that’s not the case for so-called ‘classic productivity’ AI features like sketch auto-constrain or automated drawings, “No one has intellectual property on how to constrain a sketch,” said Anagnost. “[For] that we just train away.”

This point was echoed by Hooper in relation to automated drawings, “Leveraging information that we have in Fusion about how people actually annotate drawings is not leveraging people’s core IP,” he said.

To help bring more transparency to how Autodesk is using customer data for training its AI models, Autodesk has created a series of Autodesk AI transparency cards which will be made available for each new AI feature. “These labels will provide you a clear overview of how each AI feature is built, the data that is being used, and the benefits that the feature offers,” said Arasu.

Of course, some firms will not want to share their data under any circumstances. Anagnost believes that this may lead to a bifurcated business model with customers, where Autodesk builds some foundational intelligence into its models and then licenses them to individual customers so they can be fine-tuned with private data.

AI compute

AI requires substantial processing power to function efficiently, particularly when it comes to training. With Autodesk AI, everything is currently being done in the cloud. This can be expensive but, as Anagnost boasted: “We have negotiating power with AWS that no customer would have with AWS.”

Relying on the cloud means that in order to use features in Fusion like auto constraints or drawing automation, you must be connected to the Internet.

This might not be the case forever, however. Arasu told AEC Magazine that AI inferencing [the process of using a trained AI model to make predictions or decisions based on new data] could go local. She noted some of Autodesk’s customers have powerful workstations on their desktops, implying that by using the cloud for compute would mean a waste of their own resources.

All about the data

It goes without saying that data is a critical component of Autodesk’s AI strategy, particularly when it comes to what Autodesk calls outcome-based BIM, as Mangon explained, “Making your data from our existing products available to the Forma Industry Cloud will create a rich data model that powers an AI-driven approach centred on project outcomes, so you can optimise decisions about sustainability, cost, construction time and even asset performance at the forefront of the project.”

To fully participate in Autodesk’s AI future, customers will need to get their data into the cloud-based common data environment, Autodesk Docs, which some customers are reluctant to do, for fear of being locked in with limited data access only through APIs.

Autodesk Docs can be used to manage data from AutoCAD, Revit, Tandem, Civil 3D, Autodesk Workshop XR, with upcoming support for Forma. It also integrates with third-party applications including Rhino, Grasshopper, Microsoft Power BI and soon Tekla Structures.

The starting point for all of this is files but, over time, with the Autodesk AEC Data Model API, some of this data will become granular. The AEC Data Model API enables the break-up of monolithic files, such as Revit RVT and AutoCAD DWG, into ‘granular object data’ that can be managed at a sub-file level.

“With the AEC Data Model API, you can glimpse into the future where data is not just an output, but a resource,” said Sasha Crotty, Sr. Director, AEC Data, Autodesk. “We are taking the information embedded in your Revit models and making it more accessible, empowering you to extract precisely the data you need without having to dive back into the model each time you need it.”

Crotty gave the example of US firm Avixi, which is using the API to extract Revit data and gain valuable insights through Power BI dashboards.

When the AEC Data Model API launched in June, it allowed the querying of key element properties from Revit RVT files. Autodesk is now starting to granularize the geometry, and at AU it announced it was making Revit geometric data available in a new private beta. For more on the AEC Data Model API read this AEC Magazine article.

Autodesk Docs is also being used to feed data into Forma Board, a digital whiteboard and collaboration tool that allows project stakeholders to present and discuss concepts.

“Forma Board lets you pull in visuals from Forma and other Autodesk products through Docs, and now you can demonstrate the impact of sun or noise, ask for feedback on specific concepts, and much more,” said Bunszel.

Revit also got some airtime, but the news was a little underwhelming. Bunszel shared her favourite Revit 2025 update – the ability to export to PDF in the background without stopping your work. Meanwhile, manufacturing customers were being shown the future, with new features coming to Inventor 2026 such as associative assembly mirror and part simplification.

In the press conference Anagnost reiterated how Forma is different to Revit. “It is driven by outcomes,” he said. “We not trying to redo Revit in the cloud.”

Anagnost added that Forma is going to start moving downstream into things that Revit ‘classically does well. “It doesn’t mean it has to swallow all of Revit, and you know that would take a long time, but it can certainly do things that that Revit does today as it expands,” he said.

An iterative future

Autodesk is beginning to add clarity to its AI strategy. It is addressing AI from two angles: bottom up, bringing automation to repetitive and error prone tasks, and top down with technologies like Project Bernini that in the future could fundamentally change the way designers and engineers work. The two will eventually meet in the middle.

Autodesk is keen to use AI to deliver practical solutions and the automation of drawings and constraints in Fusion should deliver real value to many firms right now, freeing up skilled engineers at a time when they are in short supply.

We expect automated drawings will find their way into Autodesk AEC products soon, but it’s hard to tell if Autodesk has any concrete plans to use AI for modelling productivity.

As to pushing data into Autodesk Docs to get the maximum benefit out of AI, the fear that some customers have of getting trapped in the cloud is unlikely to go away any time soon.

Meanwhile, it’s clear there’s still a long way to go before the AI foundation models being explored in Project Bernini can deliver CAD geometry with ‘high accuracy and precision’.

While Bernini is starting to understand how to create basic geometry, the 3D models need more detail, and Autodesk must also work out how they can be of practical use inside CAD. With rapid advances in text-to-image AI, one also wonders what additional value text-to-CAD might bring to concept design. One could also ask whether product designers, architects or engineers would even want to use something like this to kickstart their design process. As the technology is still so embryonic it’s very hard to tell. It’s also important to remember that Bernini is a proof-of-concept, designed to explore what’s possible, rather than a practical application.

Meanwhile, as Autodesk continues to develop the complex AI training methods, there’s also the challenge of sourcing data for training. It will be interesting to see how Autodesk’s trust relationship with customers plays out.

While Autodesk’s long-term plan is to get multiple foundation models to talk together, this doesn’t mean we are heading for true design automation any time soon.

At AU Anagnost admitted that the day where AI can automatically deliver final outcomes from an initial specification is further away than one might think. “For those of you who are trying to produce an epic work of literature with ChatGPT, you know you have to do it iteratively,” he said. That same iterative process will apply to AI for design for some time to come.

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