At AU 2025, Autodesk took a significant step forward in its AI journey, extending far beyond the slide-deck ambitions of previous years.

During CEO Andrew Anagnost’s keynote, the company unveiled brand-new AI tools in live demonstrations using pre-beta software. It was a calculated risk — particularly in light of recent high-profile hiccups from Meta — but the reasoning was clear: Autodesk wanted to show it has tangible, functional AI technology and it will be available for customers to try soon.

The headline development is ‘neural CAD’, a completely new category of 3D generative AI foundation models that Autodesk says could automate up to 80–90% of routine design tasks, allowing professionals to focus on creative decisions rather than repetitive work. The naming is very deliberate, as Autodesk tries to differentiate itself from the raft of generic AEC-focused AI tools in development.

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neural CAD AI models will be deeply integrated into BIM workflows through Autodesk Forma, and product design workflows through Autodesk Fusion. They will ‘completely reimagine the traditional software engines that create CAD geometry.’

Autodesk is also making big AI strides in other areas. Autodesk Assistant is evolving beyond its chatbot product support origins into a fully agentic AI assistant that can automate tasks and deliver insights based on natural-language prompts.

Big changes are also afoot in Autodesk’s AEC portfolio – developments that will have a significant impact on the future of Revit.

The big news was the release of Forma Building Design, a brand-new tool for LoD 200 detailed design (learn more in this AEC Magazine article). Autodesk also announced that its existing early-stage planning tool, Autodesk Forma, will be rebranded as Forma Site Design and Revit will gain deeper integration with the Forma industry cloud, becoming Autodesk’s first Connected client.

neural CAD

neural CAD marks a fundamental shift in Autodesk’s core CAD and BIM technology. As Anagnost explained, “The various brains that we’re building will change the way people interact with design systems.”

Unlike general-purpose large language models (LLMs) such as ChatGPT and Claude, or AI image generation models like Stable Diffusion and Nano Banana, neural CAD models are specifically designed for 3D CAD. They are trained on professional design data, enabling them to reason at both a detailed geometry level and at a systems and industrial process level.

neural CAD marks a big leap forward from Project Bernini, which Autodesk demonstrated at AU 2024. Bernini turned a text, sketch or point cloud ‘prompt’ into a simple mesh that was not best suited for further development in CAD. In contrast, neural CAD delivers ‘high quality’ ‘editable’ 3D CAD geometry directly inside Forma or Fusion, just like ChatGPT generates text and Midjourney generates pixels.

Autodesk has so far presented two types of neural CAD models: ‘neural CAD for geometry’, which is being used in Fusion and ‘neural CAD for buildings’, which is being used in Forma.

For Fusion, there are two AI model variants, as Tonya Custis, senior director, AI research, explained, “One of them generates the whole CAD model from a text prompt. It’s really good for more curved surfaces, product use cases. The second one, that’s for more prismatic sort of shapes. We can do text prompts, sketch prompts and also what I call geometric prompts. It’s more of like an auto complete, like you gave it some geometry, you started a thing, and then it will help you continue that design.”

On stage, Mike Haley, senior VP of research, demonstrated how neural CAD for geometry could be used in Fusion to automatically generate multiple iterations of a new product, using the example of a power drill.

“Just enter the prompts or even drawing and let the CAD engines start to produce options for you instantly,” he said. “Because these are first class CAD models, you now have a head start in the creation of any new product.”

It’s important to understand that the AI doesn’t just create dumb 3D geometry – neural CAD also generates the history and sequence of Fusion commands required to create the model. “This means you can make edits as if you modelled it yourself,” he said.

Meanwhile, in the world of BIM, Autodesk is using neural CAD to extend the capabilities of Forma Building Design to generate BIM elements.

The current aim is to enable architects to ‘quickly transition’ between early design concepts and more detailed building layouts and systems with the software ‘autocompleting’ repetitive aspects of the design.

Instead of geometry, ‘neural CAD for buildings’ focuses more on the spatial and physical relationships inherent in buildings as Haley explained. “This foundation model rapidly discovers alignments and common patterns between the different representations and aspects of building systems.

“If I was to change the shape of a building, it can instantly recompute all the internal walls,” he said. “It can instantly recompute all of the columns, the platforms, the cores, the grid lines, everything that makes up the structure of the building. It can help recompute structural drawings.”

At AU, Haley demonstrated ‘Building Layout Explorer’, a new AI-driven feature coming to Forma Building Design. He presented an example of an architect exploring building concepts with a massing model, “As the architect directly manipulates the shape, the neural CAD engine responds to these changes, auto generating floor plan layouts,” he said.

But, as Haley pointed out, for the system to be truly useful the architect needs to have control over what is generated, and therefore be able to lock down certain elements, such as a hallway, or to directly manipulate the shape of the massing model.

“The software can re-compute the locations and sizes of the columns and create an entirely new floor layout, all while honouring the constraints the architect specified,” he said.

This feels like a pivotal moment in Autodesk’s AI journey, as the company moves beyond ambitions and experimentation into production-ready AI that is deeply integrated into its core software

Of course, it’s still very early days for neural CAD and, in Forma, ‘Building Layout Explorer’ is just the beginning.

Haley alluded to expanding to other disciplines within AEC, “Imagine a future where the software generates additional architectural systems like these structural engineering plans or plumbing, HVAC, lighting systems and more.”

In the future, neural CAD in Forma will also be able to handle more complexity, as Custis explains. “People like to go between levels of detail, and generative AI models are great for that because they can translate between each other. It’s a really nice use case, and there will definitely be more levels of detail. We’re currently at LoD 200.”

The training challenge

neural CAD models are trained on the typical patterns of how people design. “They’re learning from 3D design, they’re learning from geometry, they’re learning from shapes that people typically create, components that people typically use, patterns that typically occur in buildings,” said Haley.

In developing these AI models, one of the biggest challenges for Autodesk has been the availability of training data. “We don’t have a whole internet source of data like any text or image models, so we have to sort of amp up the science to make up for that,” explained Custis.

For training, Autodesk uses a combination of synthetic data and customer data. Synthetic data can be generated in an ‘endless number of ways’, said Custis, including a ‘brute force’ approach using generative design or simulation.

Customer data is typically used later-on in the training process. “Our models are trained on all data we have permission to train on,” said Amy Bunszel, EVP, AEC.

But customer data is not always perfect, which is why Autodesk also commissions designers to model things for them, generating what chief scientist Daron Green describes as gold standard data. “We want things that are fully constrained, well annotated to a level that a customer wouldn’t [necessarily] do, because they just need to have the task completed sufficiently for them to be able to build it, not for us to be able to train against,” he said.

Of course, it’s still very early days for neural CAD and Autodesk plans to improve and expand the models, “These are foundation models, so the idea is we train one big model and then we can task adapt it to different use cases using reinforcement learning, fine tuning. There’ll be improved versions of these models, but then we can adapt them to more and more different use cases,” said Custis. In the future, customers will be able to customise the neural CAD foundation models, by tuning them to their organisation’s proprietary data and processes. This could be sandboxed, so no data is incorporated into the global training set unless the customer explicitly allows it.

“Your historical data and processes will be something you can use without having to start from scratch again and again, allowing you to fully harness the value locked away in your historical digital data, creating your own unique advantages through models that embody your secret source or your proprietary methods,” said Haley.

Agentic AI: Autodesk Assistant

When Autodesk first launched Autodesk Assistant, it was little more than a natural language chatbot to help users get support for Autodesk products.

Now it’s evolved into what Autodesk describes as an ‘agentic AI partner’ that can automate repetitive tasks and help ‘optimise decisions in real time’ by combining context with predictive insights.

Autodesk demonstrated how in Revit, Autodesk Assistant could be used to quickly calculate the window to wall ratio on a particular façade, then replace all the windows with larger units. The important thing to note here is that everything is done though natural language prompts, without the need to click through multiple menus and dialogue boxes.

Autodesk Assistant can also help with documentation in Revit, making it easier to use drawing templates, populate title blocks and automatically tag walls, doors and rooms. While this doesn’t yet rival the auto-drawing capabilities of Fusion, when asked about bringing similar functionality to Revit, Bunszel noted, ‘We’re definitely starting to explore how much we can do.’

Autodesk also demonstrated how Autodesk Assistant can be used to automate manual compliance checking in AutoCAD, a capability that could be incredibly useful for many firms.

“You’ll be able to analyse a submission against your drawing standards and get results right away, highlighting violations and layers, lines, text and dimensions,” said Racel Amour, head of generative AI, AEC.

Meanwhile, in Civil 3D it can help ensure civil engineering projects comply with regulations for safety, accessibility and drainage, “Imagine if you could simply ask the Autodesk Assistant to analyse my model and highlight the areas that violate ADA regulations and give me suggestions on how to fix it,” said Amour.

So how does Autodesk ensure that Assistant gives accurate answers? Anagnost explained that it takes into account the context that’s inside the application and the context of work that users do.

“If you just dumped Copilot on top of our stuff, the probability that you’re going to get the right answer is just a probability. We add a layer on top of that that narrows the range of possible answers.”

“We’re building that layer to make sure that the probability of getting what you want isn’t 70%, it’s 99.99 something percent,” he said.

While each Autodesk product will have its own Assistant, the foundation technology has also been built with agent-to-agent communication in mind – the idea being that one Assistant can ‘call’ another Assistant to automate workflows across products and, in some cases, industries.

“It’s designed to do three things: automate the manual, connect the disconnected, and deliver real time insights, freeing your teams to focus on their highest value work,” said CTO, Raji Arasu.

In the context of a large hospital construction project, Arasu demonstrated how a general contractor, manufacturer, architect and cost estimator could collaborate more easily through natural language in Autodesk Assistant. She showed how teams across disciplines could share and sync select data between Revit, Inventor and Power Bi, and manage regulatory requirements more efficiently by automating routine compliance tasks. “In the future, Assistant can continuously check compliance in the background. It can turn compliance into a constant safeguard, rather than just a one-time step process,” she said.

Arasu also showed how Assistant can support IT administration — setting up projects, guiding managers through configuring Single Sign-On (SSO), assigning Revit access to multiple employees, creating a new project in Autodesk Construction Cloud (ACC), and even generating software usage reports with recommendations for optimising licence allocation.

Agent-to-agent communication is being enabled by Model Context Protocol (MCP) servers and Application Programming Interfaces (APIs), including the AEC data model API, that tap into Autodesk’s cloud-based data stores.

APIs will provide the access, while Autodesk MCP servers will orchestrate and enable Assistant to act on that data in real time.

As MCP is an open standard that lets AI agents securely interact with external tools and data, Autodesk will also make its MCP servers available for third-party agents to call.

All of this will naturally lead to an increase in API calls, which were already up 43% year on year even before AI came into the mix. To pay for this Autodesk is introducing a new usage-based pricing model for customers with product subscriptions, as Arasu explains, “You can continue to access these select APIs with generous monthly limits, but when usage goes past those limits, additional charges will apply.”

But this has raised understandable concerns among customers about the future, including potential cost increases and whether these could ultimately limit design iterations.

The human in the loop

Autodesk is designing its AI systems to assist and accelerate the creative process, not replace it. The company stresses that professionals will always make the final decisions, keeping a human firmly in the loop, even in agent-to-agent communications, to ensure accountability and design integrity.

“We are not trying to, nor do we aspire to, create an answer, “says Anagnost. “What we’re aspiring to do is make it easy for the engineer, the architect, the construction professional – reconstruction professional in particular – to evaluate a series of options, make a call, find an option, and ultimately be the arbiter and person responsible for deciding what the actual final answer is.”

AI computation

It’s no secret that AI requires substantial processing power. Autodesk trains all its AI models in the cloud, and while most inferencing — where the model applies its knowledge to generate real-world results — currently happens in the cloud, some of this work will gradually move to local devices.

This approach not only helps reduce costs (since cloud GPU hours are expensive) but also minimises latency when working with locally cached data.

AI research

Autodesk also gave a sneak peek into some of its experimental AI research projects. With Project Forma Sketch, an architect can generate 3D models in Forma by sketching out simple massing designs with a digital pencil and combining that with speech. In this example, the neural CAD foundation model interacts with large language models to interpret the stream of information.

Elsewhere, Amour showed how Pointfuse in Recap Pro is building on its capability to convert point clouds into segmented meshes for model coordination and clash detection in Revit. “We’re launching a new AI powered beta that will recognise objects directly from scans, paving the way for automated extraction, for building retrofits and renovations,” she said.

Autodesk has also been working with global design, engineering, and consultancy firm Arcadis to pilot a new technology that uses AI to see inside walls to make it easier and faster to retrofit existing buildings.

Instead of destructive surveys, where walls are torn down, the AI uses multimodal data – GIS, floor plans, point clouds, Thermal Imaging, and Radio Frequency (RF) scans – to predict hidden elements, such as mechanical systems, insulation, and potential damage.

The AI-assisted future

AU 2025 felt like a pivotal moment in Autodesk’s AI journey. The company is now moving beyond ambitions and experimentation into a phase where AI is becoming deeply integrated into its core software.

With the neural CAD and Autodesk Assistant branded functionality, AI will soon be able to generate fully editable CAD geometry, automate repetitive tasks, and gain ‘actionable insights’ across both AEC and product development workflows.

As Autodesk stresses, this is all being done while keeping humans firmly in the loop, ensuring that professionals remain the final decision-makers and retain accountability for design outcomes.

Importantly, customers do not need to adopt brand new design tools to get onboard with Autodesk AI. While neural CAD is being integrated into Forma and Fusion, users of traditional desktop CAD/BIM tools can still benefit through Autodesk Assistant, which will soon be available in Revit, Civil 3D, AutoCAD, Inventor and others.

With Autodesk Assistant, the ability to optimise and automate workflows using natural-language feels like a powerful proposition, but as the technology evolves, the company faces the challenge of educating users on its capabilities — and its limitations.

Meanwhile, data interoperability remains front and centre, with Autodesk routing everything through the cloud and using MCP servers and APIs to enable cross-product and even cross-discipline workflows.

It’s easy to imagine how agent-to-agent communication might occur within the Autodesk world, but AEC workflows are fragmented, and it remains to be seen how this will play out with third parties.

Of course, as with other major design software providers, fully embracing AI means fully committing to the cloud, which will be a leap of faith for many AEC firms.

From customers we have spoken with there remain genuine concerns about becoming locked into the Autodesk ecosystem, as well as the potential for rising costs, particularly related to increased API usage. ‘Generous monthly limits’ might not seem so generous once the frequency of API calls increase, as it inevitably will in an iterative design process. It would be a real shame if firms end up actively avoiding using these powerful tools because of budgetary constraints.

Above all, AU is sure to have given Autodesk customers a much clearer idea of Autodesk’s long-term vision for AI-assisted design. There’s huge potential for Autodesk Assistant to grow into a true AI agent while neural CAD foundation models will continue to evolve, handling greater complexity, and blending text, speech and sketch inputs to further slash design times.

We’re genuinely excited to see where this goes, especially as Autodesk is so well positioned to apply AI throughout the entire design build process.

Main image: Mike Haley, senior VP of research, presents the AI keynote at Autodesk University 2025  

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London-based KREOD is planning to bring “aerospace-grade precision” to the built environment, with its new KREODx platform which has just launched in beta.

The software harnesses Parasolid from Siemens Digital Industries Software, a geometric modelling kernel that is typically found inside mechanical CAD tools such as Dassault Systèmes Solidworks, Siemens Solid Edge, and Siemens NX.

The software combines Design for Manufacture and Assembly (DfMA) principles with a building-centric approach to Product Lifecycle Management (PLM) — a process commonly used in manufacturing to manage a product’s data, design, and development throughout its entire lifecycle.

KREODx is said to be powered by “Intelligent Automation” with parametric design and engineering workflows that “eliminate errors and accelerate delivery”.

The software offers full support for Bill of Materials (BoM) to deliver what the company describes as a single source of truth for costs, materials, and procurement, giving transparency from model to assembly.

According to the company, KREODx is also aligned with the circular economy, extending building lifespans, reducing waste, and enabling re-use and adaptability over time.

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The building envelope has always been one of architecture’s most demanding battlegrounds. A façade is expected to satisfy multiple, often conflicting requirements. It must express design intent, meet performance targets for energy efficiency, comfort and daylight, and comply with regulations.

Traditionally, assessments to ensure these requirements are met have been left until late on in projects, once a design is largely fixed and alterations become expensive.

Dublin-based FenestraPro was created to address this issue, giving architects direct access to façade performance tools inside of their existing BIM workflows and when their decisions can most optimally influence outcomes.

Established in 2012 by technologists Simon Whelan and Dave Palmer, FenestraPro emerged from a frustration with digital analysis tools that were either too specialist for day-to-day design work or too disconnected from the platforms that architects actually use.

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The goal was to bring performance data into the design process itself, enabling architects to weigh the consequences of their choices while still sketching and modelling.

Today, FenestraPro is used by international firms such as AECOM, Jacobs and HKS, where architects and engineers rely on it to help close the gap between aesthetic intent and energy performance.

Face value

FenestraPro’s technology centres on façade analysis and offers deep integration with Autodesk environments. Its best-known product, FenestraPro for Revit, runs as an add-on and allows users to test glazing proportions, shading devices and material selections without leaving their BIM model.

A partner application extends similar functionality into Autodesk’s emerging Forma conceptual design platform, enabling performance analysis from the massing stage onwards. In this way, designers can quickly evaluate how orientation, window-to-wall ratios or shading strategies will affect daylight levels and energy use.

Instead of waiting on external reports, the system provides immediate feedback, with colour-coded surfaces and dynamic charts that highlight potential problem areas such as glare or excessive solar gain.

The software deliberately avoids imposing the heavy computational demands associated with full building simulation tools. Instead, it delivers a lightweight, responsive engine designed for iteration.

This makes it possible for users to compare multiple façade options in quick succession, guiding design choices before geometry becomes too fixed. The package also incorporates a database of more than a thousand glazing products, complete with accurate thermal and solar properties. Recent integrations, such as a link with Vitro Architectural Glass, allow data from manufacturers’ specification platforms to flow directly into the FenestraPro environment, grounding analysis in real-world products rather than generic assumptions.

As projects evolve, the software continues to add value. It supports detailed façade modelling inside Revit, from panelisation through to mullion layouts, while maintaining live performance feedback.

One notable feature is its ability to identify errors or weaknesses in BIM energy models – issues that can compromise downstream analysis. By flagging these early, the tool ensures that data exported from Revit is both reliable and compliant. Reports and outputs can then be generated for a range of uses, from compliance submissions to client presentations.

Design teams can evaluate options in minutes, not days, which accelerates iteration and avoids costly late-stage changes. Building owners get the assurance that the building envelope has been optimised for operational energy consumption and improved occupant comfort. Meanwhile, architects can have greater confidence that their aesthetic choices will work in harmony with performance/ sustainability requirements.

Connecting the dots

FenestraPro does not aim to replace engineering-grade simulation packages. Instead, it focuses on providing architects with the early intelligence they need to make smart façade decisions. By connecting the dots between early-stage exploration in Forma and detailed design in Revit, the platform promotes a joined-up approach to performance.

With sustainability targets becoming stricter and clients demanding more accountability, tools that embed envelope analytics into mainstream BIM workflows are gaining in importance.

FenestraPro’s strategy is to complement existing design environments, rather than reinvent them, positioning itself as a pragmatic but powerful partner in the pursuit of sustainable architecture.

Prices start at $29 per month for Envelope Analysis in Forma and $149 per month for a Premium offering, which adds Revit integration, detailed thermal analysis, carbon benchmarking, model checking and export tools. Discounts are available for teams.

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Vectorworks has undergone some big changes over the last couple of years, as it navigates the shift to a more subscription-based model for customers and, more recently, adapts to new leadership. With Jason Pletcher now at the company’s helm, there could be further transformation ahead.

Pletcher was announced as the new CEO of Vectorworks in February 2025, taking the reins from Dr Biplab Sarkar, who retired in March after an impressive 25-year tenure at the company.

Pletcher came to Vectorworks from another Nemetschek brand, GoCanvas, where he served as chief operating and financial officer and, according to Nemetschek executives, was instrumental in almost quadrupling GoCanvas’ business over a 5-year period.

Hopes are presumably high that he can pull off a similar trick at Vectorworks, improving its business and expanding its market reach.

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The new Vectorworks CEO has wasted no time in emphasising his conviction that design creativity should drive business results, rather than be hindered by software limitations. That’s an interesting statement, perhaps suggesting that Vectorworks might be readying itself to explore the world of cloud-based services, a market in which GoCanvas already operates as a provider of mobile field work management software.

Moving forward

One thing that hasn’t changed, however, is Vectorworks’ commitment to providing its customers with an annual refresh of product capabilities – with the additional flourish this year of declaring Vectorworks 2026 as its most “forward thinking software version yet”.

As Pletcher put it: “Designers are ambitious and Vectorworks 2026 offers the tools to transform their big ideas into reality. Our latest version allows designers to work more efficiently, break free from busy work, automate manual processes and unleash their design freedom, so their best work can move forward.”

The overarching themes of this version include integrating sustainability metrics, enhancing collaboration and reducing manual and repetitive tasks through smarter automation.

On that last point, various updates across the portfolio – which includes the Architect, Landmark, Spotlight and Design Suite products – are engineered to automate routine adjustments, increase productivity and give designers more time for exploration and design refinement.

For example, the automated Depth Cueing feature is designed to improve the clarity and spatial depth of drawings with minimal user intervention, dynamically adjusting the visual properties of objects based on their distance from the viewer in both Hidden Line and Shaded viewports.

This includes the automatic manipulation of line weights, tonal values and pixel transparency, causing objects farther away to appear lighter or fainter, while foreground elements remain prominent. This feature is most impactful for generating presentation-quality elevations and sections directly from a model, significantly improving the graphical output for design review and client communication.

With Worksheet User Interface and Slicing, meanwhile, customers will see a new ribbon-style toolbar that provides them with a more intuitive interface for worksheet operations. The new slicing capability allows users to split large, complex reports into smaller, linked sections – particularly useful for controlling page layouts, as it ensures data fits neatly within specified print areas without manual reformatting. The interface now supports pinned headers that remain visible during scrolling. These updates make creating complex reports and documents more manageable, according to Vectorworks executives.

Elsewhere, File Health Checker is a new palette designed to maintain project performance and stability, but only available to subscription customers. This diagnostic tool proactively scans active documents for issues likely to degrade performance (such as hidden geometry or resource inefficiencies, for example). The workflow presents users with smart suggestions to resolve these problems, many of which can be executed with a single click. The aim here is to tackle a common pain point in collaborative projects, where imported third-party files can introduce performance-degrading data and even lead to file corruption.

When it comes to Vectorworks’ own graphical scripting tool, Marionette, key updates have been introduced to streamline the process of creating custom parametric objects and workflows. Marionette supports Python-powered nodes, making execution faster, and also has expanded Python library support, supporting access to a large ecosystem of existing Python libraries for complex data manipulation, geometric calculations and interoperability tasks. Vectorworks executives hope this streamlining will make Marionette a more direct competitor to McNeel Grasshopper and Autodesk Dynamo.

Finally, 3D modelling gets a new Offset Face mode within the Push/Pull tool, to enable simultaneous offsetting of multiple planar and non-planar faces on a 3D model. Users can adjust multiple surfaces at one time, without having to recreate dependent features such as fillets. The tool also provides a real-time preview and allows for on-the-fly parameter adjustments.

Architect-specific enhancements

In the Vectorworks Architect 2026 product, updates focus on advanced BIM workflows and integrated sustainability analysis. For example, there are now tools to assist in designing in line with certifications such as LEED and BREEAM and in compliance with regulations such as the UK’s Biodiversity Net Gain (BNG) law.

A new sustainability dashboard provides a number of environmental analysis tools via one interface. It provides real-time monitoring of sustainability metrics as a design evolves, tracking specific data points including embodied carbon calculations, urban greening scores, biomass density and BNG.

A door and window assembly tool supports the creation of complex architectural openings, enabling users to combine elements such as doors, windows, symbols and panels, into single, unified assembly objects. (Previously, this was an error-prone process that often omitted data from schedules and quantity take-offs). This new tool replaces manual workarounds with fully parametric and data-rich objects.

New detailing capabilities for 2D graphical representation of walls, doors, and windows, allows for the customisation of 2D graphics at multiple detail levels, ensuring construction documents appear exactly as intended. By automating the creation of high-quality, standards-compliant drawings, the tool helps maintain consistency and accuracy across document sets while saving time.

Vectorworks’ cloud services can process Revit and IFC file imports, offloading the processing of large files, so that workstations aren’t locked up for 30 minutes

Data Manager, meanwhile, now has an enhanced focus on accelerating and simplifying BIM workflows. The tool’s primary role is to automate data standards compliance. This version streamlines Industry Foundation Classes (IFC) data, mapping across different versions and driving data compliance with project-specific or industry-wide BIM standards.

Landmark for landscaping

Vectorworks is the industry’s only BIM tool with a dedicated ‘flavour’ for landscaping design. In this release, there’s a new Plant Style Manager, a spreadsheetstyle tool that helps users to build, manage and customise a dedicated plant library. It supports batch editing, importing data from nursery partners and plant placement. Since it’s based on a centralised system, this capability drives data consistency from design through to procurement.

The existing Tree tool is improved to support the creation of more realistic and data-rich tree models for regulation-compliant landscape design. The most significant enhancements are support for Maxon Plant Geometry, image props and 3D symbols. Existing trees can be integrated with geographic information system (GIS) data.

Grade Objects have been enhanced and can be created using curves and polylines in both 2D and 3D views. The tool integrates with data tags, allowing for instant labelling of elevations and streamlined reporting of site grading information.

Finally, the Massing Model tool has been updated to accommodate the planning of mixed-use structures. The tool now allows designers to define unique heights, classes and usages for individual floors within a single massing model object.

Spotlight for entertainment

The one market in which Vectorworks stands alone is in providing CAD/BIM capabilities for entertainment design, particularly stage and theatre design, covering everything from lighting and mixing desks to stage elements.

The updates in Spotlight 2026 focus on streamlining the design of advanced A/V equipment and on improving collaborative workflows for live events and installations.

There’s a new LED Wall creation tool, which can create walls of virtually any shape, including flat, curved and three dimensional forms. The tool supports the ability to calculate technical specifications, such as power and data requirements, overall size and weight, and pixel resolution.

A new, dedicated tool for common rigging hardware (specifically clamps and side arms) has been added, replacing the previous method of using generic symbols or complex grouped objects, which often lead to inaccurate inventory counts and imprecise geometry in rigging plots, requiring significant manual verification.

Spotlight now supports the MVRxchange Protocol, which powers a local network protocol allowing users to instantly share, commit and request My Virtual Rig (MVR) files with other connected applications, such as lighting consoles or pre-visualisation software.

The Showcase feature for real-time visualisation has had several enhancements including animated fog for creating atmospheric effects, false colour rendering for technical lighting analysis and DMX-driven control of lighting devices. There are also user interface enhancements for tuning the output.

Future directions

Vectorworks is fleshing out its formative cloud services offering. In this release, it aims to offload some of the processing work from the desktop to the cloud. There’s a new ‘Cloud Status’ widget integrated directly into the Vectorworks view bar, which provides real-time updates on the progress of cloud processing jobs and direct access to results without leaving the desktop application.

For subscribers only, Vectorworks’ cloud services can process Revit and IFC file imports, offloading the processing of large files, so that workstations aren’t locked up for 30 minutes. Users can work on, uninterrupted.

For now, there seems to be a pretty good spread of features for all users in the various disciplines that Vectorworks targets. There is a clear drive to assist with automation and reporting, increasing documented accuracy and productivity.

Those features that are limited to subscribers, we would suggest, are highly desirable and fit well with the company’s drive to get customers onto subscription contracts.

With a new CEO on board – and one recruited from a SaaS provider – we anticipate an increasing effort to convert the customer base to subscription payments over the coming years, along with greater cloud integration.

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Bluebeam has announced Bluebeam Max, a premium subscription plan due to launch early 2026 that is designed to bring a range of AI features to its PDF-based collaboration and markup tool Revu.

A new Anthropic Claude integration will bring natural-language AI prompts directly into Revu, allowing users to automate tasks and turn markup data into ‘actionable insights’.

Building on its recent acquisition of Firmus AI, Bluebeam is also introducing AI-Review and AI-Match — intelligent tools that help uncover design issues early, detect scope gaps, and compare drawings with ‘unprecedented accuracy’.

For large-scale infrastructure projects, a new Stitching feature automatically combines multiple drawing sheets into a ‘single navigable view’.

Bluebeam has also added advanced MagicWand markup tools, along with new ‘Convert to,’ ‘Duplicate as,’ and ‘Offset’ actions, helping users automate repetitive markups and speed up takeoffs with fewer manual clicks.

Rounding out the new offering, Connected Sessions with Revit now bridge 2D markups and 3D models, with a view to streamlining coordination between design and build teams.

While Bluebeam Max will initially integrate with Anthropic Claude, the company says its use of the industry-standard Model Context Protocol (MCP) will allow future connections with other AI models – including Copilot, ChatGPT, Perplexity, and Gemini — as soon as those platforms offer desktop apps with MCP integration.

In addition to Bluebeam Max, the company has announced a series of updates available to all Revu subscribers, aimed at improving collaboration, mobility, and document management across projects.

A new Task Link feature connects Revu markups directly with field tasks in GoCanvas, giving office and field teams real-time visibility into project progress.

Meanwhile, Intelligent Search has been enhanced to support natural-language queries across all Studio Projects folders — whether accessed via Revu or the web — helping teams quickly locate files, comments, and markups.

There are also improvement for mobile users. On iOS, teams can now access full Studio Project functionality, work offline with sync support, and manage local files. Android users will gain these same offline and local access capabilities in early 2026.

Bluebeam has also added a DocuSign integration, enabling secure e-signatures directly within Studio Projects without the need to download or re-upload documents. Finally, new integrations with Procore, OneDrive, and SharePoint allow users to open, mark-up, and sync files seamlessly across platforms, further streamlining project workflows.

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Autodesk has introduced neural CAD, a new category of 3D generative AI foundation models coming to Fusion and Forma, which the company says will “completely reimagine the traditional software engines that create CAD geometry” and “automate 80 to 90% of what you [designers] typically do.”

Unlike general-purpose large language models (LLMs) such as ChatGPT, Gemini, and Claude, neural CAD models are trained on professional design data, enabling them to reason at both a detailed geometry level and at a systems and industrial process level – exploring ideas like efficient machine tool paths or standard building floorplan layouts.

According to Mike Haley, senior VP of research, Autodesk, neural CAD models are trained on the typical patterns of how people design, using a combination of synthetic data and customer data. “They’re learning from 3D design, they’re learning from geometry, they’re learning from shapes that people typically create, components that people typically use, patterns that typically occur in buildings.”

Learn more about neural CAD and Autodesk’s evolving AI strategy in AEC Magazine’s in-depth report

Autodesk shows its AI hand

Autodesk says that in the future, customers will be able to customise the neural CAD foundation models, by tuning them to their organisation’s proprietary data and processes.

Autodesk has so far presented two types of neural CAD models: ‘neural CAD for geometry’ and ‘neural CAD for buildings’.

With neural CAD for geometry, designers using Autodesk Fusion will be able to use language, sketching or imagery to produce ‘first-class’ CAD geometry which can then be used directly in manufacturing processes.

With neural CAD for buildings architects using Forma will be able to ‘quickly transition’ between early design concepts and more detailed building layouts and systems with the software ‘autocompleting’ repetitive aspects of the design.

“If I was to change the shape of a building, it can instantly recompute all the internal walls,” says Haley. “It can instantly recompute all of the columns, the platforms, the cores, the grid lines, everything that kind of makes up the structure of the building. It can help recompute structural drawings.”

At Autodesk University this week, Autodesk will be demonstrating Project Think Aloud, a new research project that explores how generative AI neural CAD models can help with architectural blocking.

Designers create buildings by sketching with an electronic pencil and talking at the same time. “The AI is able to take the speech and the text and reason about what your intent is to produce, building directly in Forma,” says Haley.

Meanwhile, in related news, Autodesk has announced Forma Building Design, a detailed building design solution that is said to offer LOD 200/300 detail, ‘AI-powered’ automation and integrated analysis.

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HP has enhanced its construction management platform, HP Build Workspace, introducing mobile-enabled scanning and AI-powered vectorisation directly from HP DesignJet MFPs (Multifunction Printers).

HP AI Vectorization enables the conversion of raster images into ‘clean, editable’ vector drawings suitable for CAD applications.

The multi-layered AI Vectorization engine, which is trained on real architectural and construction plans, also includes object recognition so it can identify architectural elements such as doors, windows, text, and dashes.

Currently, the processing for AI vectorization is done in the cloud but next year HP Z Workstations users will be able to run jobs locally as well. According to HP, it will be up to 2x faster.

Meanwhile, through HP Click Solutions integration, AEC professionals can also ‘seamlessly print’ documents from HP Build Workspace directly to HP DesignJet printers.

HP has also launched a new large format printer, the HP DesignJet T870, which is billed as a compact, versatile 24-inch device that combines high-quality output with sustainable design.

According to HP, it’s up to 30% lighter, quieter, and more energy efficient than previous models and delivers the ‘world’s easiest multi-size printing experience’ from A4/A to A1/D, without manual media switching. It can produce an A1/D print in as little as 21 seconds.

The printer also features HP Flex Tech Inks to deliver ‘precise CAD drawings’ and ‘vibrant visuals’. With HP Click Solutions professionals can preview jobs in real time, catch errors before they happen, and send projects from ‘virtually any device’.

Finally, HP has introduced HP SitePrint SMR Prism, a new precision accessory for its 1:1 plan printing robot, HP SitePrint.

According to HP, the prism automatically rotates to maintain optimal alignment with total stations, ensuring layout accuracy of up to +/- 2mm (1/16 inch) and floor deviation marking precision down to +/- 0.8mm.

Looking ahead, HP is also set to broaden its floor deviation marking services to support new applications such as interior finishing.

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Vectorworks 2025 Update 5, the latest release of the CAD and BIM software, features a preview of AI Assistant, a new tool designed to give users ‘instant and accurate’ answers to their Vectorworks-related questions.

Available through the Help menu and the Vectorworks Home Screen, the built-in AI assistant is designed to give customers quick, context-aware answers to their questions helping them learn new features or seek guidance.

“The AI Assistant (Preview) is your partner in learning and productivity and is a significant advancement in the Vectorworks experience,” said Vectorworks vice president of product management Vlado Stanev. “It’s an intelligent tool designed to meet designers at their level, whether they’re new to the software or seasoned pros. This is just the beginning of our vision for how AI can support our users.”

The AI Assistant (Preview) represents the first phase of Vectorworks’ AI learning integration, laying the foundation for deeper AI integration across the platform. Vectorworks states that future plans include leveraging the Nemetschek AI Layer to deliver even smarter, more efficient, and increasingly adaptive solutions to address designers’ evolving needs and unique design workflows.

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Widespread adoption of 3D technology and the growth of BIM expertise have transformed AEC – but the most important output for any firm is still documentation — more specifically, the production of 2D drawings.

Before the arrival of BIM, CAD represented a way to accelerate workflows, a speedy alternative to manual drafting. It supported quick drawing, fast editing and some automation. Early dedicated AEC applications (such as the UK-developed AutoCAD AEC) provided still more acceleration, since AutoCAD came with a raft of blocked symbols, layering conventions, hatching and linetype styles. Now, we thought, we’re cooking on gas!

Then along came BIM, insisting we all model buildings in 3D and, as a by-product of this process, derive 2D line takeoffs from the geometry in order to fast-track the production of drawings. If we changed the design (in other words, the 3D model), the drawing would automatically update. BIM front-loaded the design system with more work and more decisions to be made, but at the same time, it helped improve understanding of a design, as well as offering renderings and analysis capabilities. It also fostered an explosion in the output of drawings.

Drawings are not going away – but there is certainly a movement focused on the mass-automation of their creations. Some believe they might be eliminated altogether, with the model becoming the deliverable instead. At AEC Magazine, we don’t think that will ever happen, given that in more advanced sectors such as automotive and aerospace, drawings are still produced, even in situations where fabrication is highly automated around models.

That said, a great deal of effort is dedicated to the automation of drawings, with companies including SWAPP, Graebert, Evolvelab (now part of Chaos) all developing automated BIM to 2D drawing tools.

Both Graebert and Evolvelab will be at NXT DEV in London on 12 June and Graebert’s auto drawing capabilities will be demonstrated by BIM 2.0 start-up Qonic, which has integrated them into its own product – but more on that later.

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Old drawings

But let’s not get ahead of ourselves. While it’s true that most new builds over the last four decades and more have likely been created through 2D CAD or BIM, what about all the buildings that were built before the emergence of the large digital design footprint?

These buildings are documented mostly on paper, or perhaps digitised to images, once archived through raster scanning. With refurbishment becoming an increasingly attractive option for building owners faced with sustainability regulations, wouldn’t it be a good idea to be able to automate BIM from 2D?

Long-held drawing standards and defined 2D symbolic representation give intelligent systems a language that can help 2D drawings be translated into a 3D model. Dimensions and markings can also assist in driving accuracy, in situations where perhaps the drawings are inaccurate, stretched or left askew following scanning.

Several software firms are working on building a bridge between dumb 2D drawings and intelligent 3D models. This means old drawings might be rapidly repurposed as 3D models for digital twins, layouts for facilities management, or as a baseline for refurbishment.

In the last edition we looked at how new start-up Higharc has developed an AI algorithm that can take hand-drawn sketches and convert them into fully detailed BIM.

In the case of Higharc, the AI recognises external and internal walls, doors and windows, and their dimensions, and can identify anchored floors in its American timber frame housing expert system.

This capability was created not to show off how well AI could perform this task, but because Higharc had a real problem it needed to solve. The type of companies that Higharc typically sells to are house building firms with limited in-house digital skills.

Higharc’s powerful cloud-based 3D design system models timber frame housing at fabrication-level detail and connects to ERP systems to generate costings, based on the design the customer has chosen.

Considering its impressive capabilities, Higharc is easy to learn, even where employees aren’t that familiar with CAD or digital design tools. The system’s drawing AI enables experienced builders more comfortable with hand-sketching layouts to get involved in the digital design process. It takes dumb lines and substitutes them with intelligent walls and building components that are construction-accurate and that links to the system’s ERP. Aimed at a pretty specific target customer group, Higharc may not be a 2D-to-3D solution for the masses, but it’s an interesting representation of what is enabled when AI is applied to 2D sketches.

2D-to-3D for the masses

If you search, you will find several applications that support the conversion of 2D to 3D for BIM. There’s WiseBIM, Plans2BIM, and usBIM.planAI by ACCA.

In fact, all three systems are related, since they are all powered by the 2D-to-3D technology built by Paris-based software developer WiseBIM. This uses AI to convert 2D images to Revit and IFC objects.

In addition, a new Sweden-based startup called BIMify also uses AI and supports Revit and IFC workflows. Although BIMify claims Archicad support, this is via IFC for now, while its Revit support is a lot more integrated to the format.

For this article we spoke with both WiseBIM and BIMify to discover what’s possible today. We also got a sneak peek of BIM software startup Qonic’s forthcoming auto drawing capability

Conclusion

While many people are still waiting around for new 3D BIM tools, it’s clear that development work is increasing our options, when it comes to what capabilities we can buy and how we will work in future. Drawing capabilities are a big part of that picture.

The companies developing 2D-to-3D capabilities are heavily focused on using machine learning and AI to perform this task, together with rules and configurations. It’s our understanding that Graebert’s technology is predominantly linear processing without any AI, but in the future, we fully expect to see some machine learning used in the production of auto drawings, as they scale from general arrangement (GA) to Level 400.

The key takeaway here is that dumb 2D drawings won’t stay dumb for long. If a drawing is an accurate plan, then there are simple ways to digitise that information and convert it to 3D. As for autodrawings, it’s clear that this June at NXT BLD, there will be real productivity benefits to witness first-hand.

WiseBIM – 2D-to-3D conversion for IFC and Revit

Last summer, the AEC Magazine web server almost reached a meltdown when we ran a story on Paris-based AEC software company, WiseBIM. News of the developer’s in-Revit 2D-to-3D application attracted tens of thousands of views.

In fact, WiseBIM has been leading the charge in 2D-to-3D conversion for some time, having begun its journey around 2017. Before releasing a version that works within Revit, WiseBIM promoted itself under various names—including Plans2BIM— and built its online presence across multiple platforms. Its tools were also licensed by Italian BIM software developer ACCA.

The primary use case for WiseBIM is projects that involve existing buildings, for renovation, facility management, maintenance and digital twin initiatives.

The company’s core technology relies on AI algorithms that work on pixel data from 2D plans, such as PDFs, PNGs, JPEGs, DWGs and DXFs. The software automatically identifies building elements from raster or vector input. The process involves importing the plan, setting the scale, running the AI detection for specific elements (walls, openings, slabs, roofs, columns, beams, furniture, text and so on), and then allowing users to review, edit and correct the generated model.

While initial versions attempted ‘all at once’ detection, the current approach allows for more piecemeal detection of elements (walls, then openings, and so on). This has been a deliberate choice by the developers, as Tristan Garcia, co-founder and CEO of WiseBIM, explains. “It’s actually better this way. AI does make mistakes, but now users can correct these in the workflow.”

There are two flavours of the application: one that works inside Revit, and one that operates standalone as a web service (Plans2BIM). Obviously, the Revit solution is all about delivering RVT components, while the web version aims to convert 2D to standard IFC components for generic reuse. The online variant allows for the creation and assembly of multiple floors into a single building model.

In Revit, users can specify Revit families for detected elements to ensure consistency in the generated BIM model. As Garcia explained, “In our latest version, you can specify what family you are looking for, which means, because it’s using pixel-level identification, that if in your plan, the internal walls are ten centimetres thick, you can say, ‘Okay, every wall that you identify that is between nine centimetres and 11 centimetres is a ten-centimetre wall. This helps the AI deliver homogeneous output, and model those walls in the same family.”

WiseBIM supports multiple export formats, including IFC, DXF, and CSV/ XLSX (quantity take-offs). A specific JSON format is also available for development purposes. Users can add properties (for example, materials) to building elements, such as indicating that a wall is made of concrete, and all properties can be added, such as thermal coefficients.

WiseBIM’s origins can be traced back to a patented thesis at a French research centre initially developed for delivering thermal simulation. The company has a team of nine, who are predominantly technical.

Their advice to improve the chances of a successful output is to focus on the quality of the 2D plan. This significantly impacts the accuracy of the AI detection. A minimum resolution of 100 pixels per metre is recommended. Removing noise and cropping irrelevant parts of the drawing (like legends) can also improve results. If you leave in the title block, lines around it may be identified as walls. So there is some pre-preparation required to clean up drawings.

In the translation process, certain information, such as wall height or sill height, is often not explicitly present in 2D plans. This will need to be manually set by the user during configuration.

Currently focused on architectural elements, the company plans to tackle the more complex task of converting structural and MEP drawings next year.

Plans2BIM is priced at €49 euros per month or €299 per year. The Revit add-on is $29 per month or $249 per year.

Huge interest in this technology points to significant demand for automating the conversion of existing building data into BIM models – particularly for renovation, facility management and digital twin initiatives. WiseBIM and Plans2BIM offer a compelling AI-powered solution for converting 2D plans to BIM.

While the AI’s accuracy sometimes requires user intervention, the iterative editing process and customisable features still deliver a time-saving solution over the manual alternative. There could be some rework of the standalone user interface, but it seems to work well in Revit as an add-in.

BIMify: 2D drawings and point clouds into BIM models

I first heard the term ‘BIMify’ used in relation to a feature in BricsCAD that converted dumb 3D geometry into intelligent BIM components. Now, we have a new service called BIMify, from a totally unrelated company, which is applying AI to convert dumb 2D drawings and point clouds into BIM models, mainly Revit.

Based in Sweden, BIMify is the brainchild of Aleksandar Balicevac and the result of five years of research and experimentation into reliable conversion technologies. As mentioned, BIMify is a service, rather than a software that you buy. It’s built on Balicevac’s AI code and a number of key Autodesk Forge (APS) components. While the BIMify website claims support for Archicad, this is currently via IFC, while Revit is native RVT.

BIMify takes a ‘factorylike’ approach, using machine learning and AI to batch process files, so that it’s possible to ‘feed in’ individual floors of a building and get a fully assembled Revit model out the other end. It’s even possible to have this model use your own family of parts. That means you can go from six dumb floor plan drawings to a fully editable RVT model in minutes.

BIMify supports various input formats – DWG, DXF, point cloud, PDF, image – and can output in RVT or IFC. While focusing on architecture currently, the company plans to expand into other disciplines and its team is developing features for model maintenance and seamless integration with other industry systems.

Balicevac says he is primarily focusing on Europe to start, where he estimates there are over 20-25 billion square metres of buildings, of which some 95% were built pre-BIM and will need digitising sooner or later.

As to the accuracy of the AI, he seems supremely confident of his system. As it’s working, the AI is checked against building rules, leading to what he calls ‘engineering intelligence’ – knowing standard wall thicknesses, for example, or the minimum areas for spaces like bathrooms, which improves the confidence level of the AI. It can recognise interior and exterior walls, doors, windows, slabs and so on.

The BIMify workflow

The process begins with a user providing input data for their building, specifying the type of model needed on the platform. This includes defining the purpose-based specification (for example, for space management, reconstruction, or detailed design) and the desired level of detail (LoD).

Users describe their building (type, gross area, number of levels, level heights) and assign the input 2D files to the correct levels. They can also select the desired output format. Critically, users can specify their own Revit template and families to be used in the generated model. The platform provides an instant price quote based on the building size and specification.

Automated generation uses the company’s deep learning and AI to read the input files. Machines go through the drawing or scan to identify objects like walls, doors, windows, curtain walls, slabs, plumbing fixtures, columns, and rooms. The AI aims to determine object types and their locations (and is being developed to add increased granularity, such as single/double/triple windows). Engineering intelligence is applied, with building rules used to validate and refine the AI output, as previously described.

Balicevac claims 100% accuracy here, which, if true, would certainly distinguish this tool from many other AI tools. He says that BIMify “avoids heuristic methods that rely on identifying spaces first, instead processing the full drawing (or parts) to identify objects directly.”

Some elements cannot currently be modelled automatically. These include stairs, railings, roofs, vertical openings and custom specification details, and require manual work by BIMify’s inhouse team.

The model undergoes a standardised, semi-automated quality assurance step. This ensures the delivered model is complete and meets the specified quality standards. The manual completion and QA process also provide direct feedback to the development team to improve the automation algorithms.

Balicevac also tells us that the company has clients that are moving from other BIM systems to Revit and are using their system to convert old projects, as IFC does not give them editable Revit geometry. This means taking 2D out to get 3D native RVT files, which is an extremely interesting workflow.

We find that most AI developers are very protective of their ‘secret sauce’. They like to keep quiet about how they achieve what they do, and BIMify is more tight-lipped than most.

However, the company is clearly using Autodesk APS components to build these native Revit models with real-world families, such as the Forge viewer, data exchange and, I’m guessing, Revit.io (a headless Revit in the cloud). This is probably reassuring to Revit users, but may make it hard for BIMify to tackle native Archicad, as there is no equivalent to Revit.io.

BIMify makes big claims about output accuracy. Talking with Balicevac, you get the sense that he really knows what he’s doing with AI and ML. He’s put code in place to keep the AI in check with real-world engineering constraints. Autodesk’s approach with Forge is certainly advantageous here, but additional formats will be harder to achieve. Either way, BIMify is certainly an interesting firm to follow.

Qonic: Autodrawings

In 2024, Ghent-based developer Qonic launched its BIM 2.0 platform. On the face of it, the first iteration is a cloudbased common data environment (CDE), capable of handling massive BIM models that far surpass Revit’s loading capability. It offers a really simple interface for filtering and interrogating BIM data, with intuitive sectioning and a frame rate that approaches computer-game level. Underneath, there’s a solid modelling engine that supports highly accurate editing of geometry and is aimed at the junction where architectural BIM meets construction BIM. In short, this was the starting point of what looks set to be a rapid and exciting adventure in software development.

Qonic is beefing up its platform. For the purpose of this article, we are going to focus on just one of the new introductions – and that’s the long-promised Autodrawings function.

With this goal in mind, Qonic has licensed Graebert’s Kudo DWG technology, which now comes with some autodrawing capability. It’s taking this base layer and building a powerful integration so that Qonic can ingest huge, multi-disciplinary models and quickly output 2D general assembly drawings.

When the technology was shown to me, I got the message that while the AEC industry generally recognises the necessity of drawings, executives at Qonic feel that their importance may dwindle in the future as model-based workflows become more prevalent, not to mention more accessible to a broader audience.

While I tend to agree with this idea in theory, I know from experience that it’s not always the case in practice. Our sister publication, DEVELOP3D, has plenty of readers that use Catia, Solidworks, Siemens NX and Inventor, for example, and even when they manufacture parts directly from CAD models, the production of drawings is still mandated for them. But that’s a discussion for another time.

In Qonic, the drawing generation process utilises the rich data and structure within the Qonic 3D model – derived from IFC or enriched from RVT – to produce intelligent and wellannotated 2D outputs. Graebert’s server-side automation and browserbased viewing of drawings, using its Kudo technology, is key to this new, combined cloud functionality.

Qonic’s drawing generation is primarily a one-directional output. Changes to dimensions, tags or other annotations must be made in the 3D model, which then triggers an update to the drawing. Qonic has no intention to create a full 2D editor that directly modifies the 3D model.

The automated generation works a bit like Hypermodels in Bentley iModel, with drawings generated automatically from defined section planes and templates, with the potential for scheduling this process (for example, it might take the form of nightly updates). The output is fully vectorised, allowing for export to formats including DWG and PDF. Drawings can be viewed directly within the Qonic environment, with basic annotation supported, such as adding dimensions and moving tags. A mechanism to flag outdated annotations following model updates is planned for the future.

Many firms struggle to get BIM models exactly how they want them, and resort to ‘fixing it in the drawing’. Here, Qonic is empowering users to fix inaccuracies in the model due to performance capabilities and provides automation tools for propagating changes, rather than relying on manual fixes in 2D drawings.

Initially, the focus is on producing general arrangement (GA) drawings with the goal of extending the capability to more detailed construction and design delivery drawings in the future. It’s also worth pointing out that many firms have their own internal visual styles for general arrangement drawings. Qonic will enable configurations to cater to most firms’ visual tastes for wall styles, openings and other content.

The drawing functionality will likely form part of the paid subscription options and not appear in the free version of Qonic. Pricing is not expected to be based on tokenisation or usage, although these pricing structures are used by some competitors.

Drawing generation capabilities are now in active development. The company already has working prototypes and is hoping to release the software later this year. The Qonic team will appear on the main stage at NXT BLD (London, 11 June) demonstrating this new functionality and will also be offering attendees a chilled-out exhibition space in which to relax and talk to the team.

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In May 2025, HP plans to officially launch an AI vectorisation feature for its HP Build Workspace collaboration platform, first announced in September 2024.

According to HP, it will be the first solution to use AI for converting raster images into CAD-editable documents, saving hours of manual work per drawing. The system can detect lines, polylines, arcs, and text. Once text has been extracted and indexed, users can search on that data.

The conversion service comes with a simple editor, which allows users to 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.

HP Build Workspace is also set to integrate more closely with the HP DesignJet family of large-format printers and scanners. According to HP, this enhanced connectivity will enable features such as scanning directly to HP Build Workspace for AI-powered vectorisation, improving communication and collaboration beyond traditional paper-based workflows.

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HP is also targeting May 2025 for the launch of a Flatness Measurement Service for HP SitePrint, its autonomous three-wheeled robot that prints 2D plans directly onto the floors of construction sites.

The HP SitePrint Flatness Measurement Service will allow users to measure floor flatness and print elevation corrections directly onto the floor. HP says this eliminates the need for external elevation and flatness data processing, which is traditionally done in the back office before being communicated to field teams.

The service aims to consolidate four manual steps—marking information on the floor, capturing elevation data, processing the data, and relocating elevation details—into a single streamlined workflow.

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