The Future of BIM With AI: Top Tools and Their Practical Evaluation

Outline:

1. Introduction to AI in BIM Modeling
2. Currently Available AI Tools for BIM
3. Overview of the Top AI Tools
   • Aurivus
   • PlanFinder
   • WiseBIM
   • Veras
   • Other Tools to Streamline BIM Workflows
4. Conclusions

Introduction to AI in BIM Modeling

In recent years, artificial intelligence has been increasingly integrated across diverse industries, and BIM processes are no exception. The complex and data-intensive nature of BIM makes it a natural candidate for AI-driven enhancements.

A growing ecosystem of AI-powered tools – plugins, extensions, standalone platforms, in-platform integrations – is currently transforming industry practices. While some solutions are already mature enough for daily use, there are lots of beta-stage ones that promise significant advancements in the near future, too.

So, how can professionals benefit from AI, and what are the best practices to leverage it efficiently? This article examines exactly that, analyzing notable AI applications within the BIM sectors as well as real-life examples, best practices, and considerations.

Currently Available AI Tools for BIM

*with integrations for Revit

Overview of the Top AI Tools

By leveraging AI, professionals can benefit from its advanced capabilities in numerous areas:

• Education and training;
• Workflow automation;
• Design optimization and speed of iterations;
• Predictive analytics and data-backed insights for better decision-making;
• Project management, and more.

There are just a few examples, as the capabilities continuously expand and new ways of impact are discovered.

In this section, we’ll review AI tools that our team has meticulously tested in real projects. The list below features the tools that are most suitable for the tasks carried out by BIM teams.

1. Aurivus

Aurivus specializes in training neural networks to convert point clouds into digital building models. This helps enhance the accuracy and efficiency of modeling processes in construction and architecture.

The company’s AI platform offers a unique blend of manual modeling and AI-augmented capabilities. Since it automatically recognizes and recreates in-model families (from walls and floors to pipes and trusses), Aurivus could be highly helpful for PointCloud to BIM-modelers. It can also clean point clouds, thus reducing their time and effort.

How Aurivus AI Works

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• Step 1 — Upload the point cloud to Aurivus AI.
• Step 2 — AI generates a Pre-Modeled Point Cloud with key elements detected.
• Step 3 — Open the file in Revit via the Aurivus plugin to continue modeling.

Testing and Conclusions

After testing this plugin, our team has drawn the following conclusions:

Aurivus AI is a very interesting and promising project with clear advantages, particularly its ease of use and fast performance. However, several drawbacks still prevent its full use in real projects, requiring additional verification and adjustments. In the meantime, we will continue to follow the development of this technology, as we find it both promising and worth watching.

2. PlanFinder

PlanFinder is a plugin for Autodesk Revit that utilizes AI technologies for automatic room layout generation. It enables architects and designers to quickly create and customize floor plans, thus significantly accelerating the design process.

How PlanFinder Works:

The algorithm is based on a machine learning model specifically trained to generate floor plans. The AI was trained using room layout data, including standard room sizes for different regions of Europe.

Testing and Conclusions

Our team has tested this plugin and drawn the following:

First and foremost, the PlanFinder plugin is likely well-suited for architects who design floor plans from scratch and need to generate a large number of layout options without spending too much time.

However, consider that refining a floor plan after using the plugin can take more time than manually creating a layout directly from the point cloud. Because of this, for BIM specialists involved in the building’s modeling based on point clouds, this plugin will not be useful.

3. WiseBIM

WiseBIM AI for Autodesk Revit is a plugin that uses AI to automatically convert 2D building plans into a 3D Revit model. This way, it’s designed to significantly simplify and accelerate the process of creating BIM models based on existing 2D plans.

How WiseBIM works:

• Step 1 — Import an architectural 2D plan of your level into Revit® (supported formats: DWG, DXF, PDF, JPEG, TIFF, PNG).
• Step 2 — Set the scale of the imported image.
• Step 3 — Select the image and click the WiseBIM Detection button in the Add-Ins menu.
• Step 4 — Define a few parameters (e.g., wall height, families) and run the automatic detection.
• Step 5 — Within seconds, the Revit® model is generated with elements automatically created.

Testing and Conclusions

Our team has tested this plugin and concluded the following:

The plugin is excellent for quickly creating a 3D building model from 2D plans if the building plan is of good quality (preferably, in DWG or PDF format). It saves a lot of time on generating wall sizes and accurately detects the width of doors and windows.

However, we’ve identified several drawbacks and inconsistencies that require manual fixing, such as:

• The plugin sometimes misinterprets the swing direction of doors;
• Occasional inaccuracies occur when connecting walls;
• Architectural elements like openings or curtain walls are not automatically identified;
• When using underlays based on point clouds, the plugin struggles to complete the task effectively, as point cloud quality does not meet its recognition requirements;
• The plugin allows only one type of window and one type of door to be set, which restricts design flexibility and requires manual adjustments.

All of this adds up to significant manual work and additional time spent on checking, correcting, and completing the model, making the tool less efficient from an automation perspective. In the meantime, we’ll be keeping an eye on the solution’s roadmap and the release of more advanced features.

4. Veras

Veras is an AI-powered visualization application developed by EvolveLAB. It integrates with programs such as SketchUp, Revit, Rhinoceros, and Vectorworks, thus allowing users to use a 3D model as a basis for generating visualizations.

How Veras works:

As a Revit plugin, Veras integrates smoothly into your existing workflow without the need to switch between different software.

Testing and Conclusions

Our team has given Veras the following verdict:

Veras is best suited for quick visualizations, concept presentations, or commercial proposals — however, not the final, production-ready renders.

Veras proves efficient in the rapid creation of visually appealing renders and offers high flexibility through descriptive input. However, precise control over the final output is limited, and reproducing identical renders from different angles can be challenging due to the AI-based generation.

Other Tools to Streamline BIM Workflows

While the solutions reviewed above focus primarily on AI-driven or AI-assisted functionality, a number of powerful automation and efficiency-focused tools can significantly enhance BIM workflows even without full AI capabilities. Explore them in the table below.

Conclusions

Analyzing the existing AI tools and plugins for Revit, it can be concluded that the use of artificial intelligence in BIM represents one of the most promising and rapidly developing directions.

The promise:

AI tools offer a range of undeniable advantages that encourage professionals to further explore, develop, and integrate these approaches into real-world projects. For instance, AI can significantly accelerate the generation of conceptual designs, automate object recognition in point clouds, optimize space layouts, and improve the accuracy of calculations at the early design stages.

Important considerations:

Nevertheless, this field still faces several limitations that hinder the large-scale adoption of AI solutions in practice.

Among the most critical challenges, these ones were noticed:

• The high cost of software products;
• The narrow specialization of certain tools is restricted to limited tasks;
• Difficulties in integrating them into existing workflows.

In particular, based on the tools our team attempted to implement, one of the major drawbacks was insufficient functionality of the built-in algorithms, which resulted in additional time expenditures for verification and manual adjustments.

The bottom line:

Considering the rapid pace of technological development and the growing demand for automation in the construction industry, it is reasonable to predict that in the near future, these tools will reach a qualitatively higher level.

Their application in BIM modeling is expected to become a standard practice, while the tools themselves will provide broader functionality, greater accessibility, and seamless integration with established design platforms. Therefore, it is crucial to closely monitor the progress in this domain in order to be prepared for its inevitable adoption in professional practice.