Learn how Ideate StyleManager, Ideate Explorer, and Ideate BIMLink help construction teams eliminate Revit inefficiencies — from unmanaged styles and hidden elements to manual data errors — with automated QA/QC workflows and bulk parameter editing that saves hours on every project.

How Ideate Software Is Helping Teams Improve Revit Data Management, QA/QC and Automation

In this article, Kestrel Labs explains how AI powered building code compliance can help architects check code directly inside the BIM model, reducing manual review, rework, and permitting delays. The conversation explores how computable building codes, Revit based workflows, and traceable compliance results can support faster design decisions, stronger code confidence, and a more efficient future for AEC permitting.

How Kestrel Labs Is Bringing Code Compliance Inside the BIM Model

<figure class="image"><img src="https://aecplustech-files.s3.amazonaws.com/blog/9198a462-3995-42b2-ad2b-bddb08f3649e.png" alt="Ichi helps architecture teams bring code research earlier into the design process, turning complex compliance questions into faster, cited answers." width="1080">
<figcaption spellcheck="false" data-qb-tmp-id="lt-987372" data-gramm="false">Fig. 1) Ichi helps architecture teams bring code research earlier into the design process, turning complex compliance questions into faster, cited answers.</figcaption>
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We sat down with Chinmayi Suri, Architectural Designer at DGA, and Brandon Levey, Founder and CEO of <a href="https://www.ichiplan.com/" target="_blank" rel="noopener">Ichi</a>, to learn how the two are working at the intersection of architecture and AI to tackle some of the profession's most time-consuming pain points: building code compliance, QA/QC, and the institutional knowledge that disappears when senior staff retire.&nbsp;
On a recent corporate laboratory project, the team at DGA, a Bay Area architecture firm specializing in life sciences and advanced manufacturing facilities, hit a familiar wall. Their mechanical scope carried a $250,000 line item for fire dampers, and the client wanted that cost justified before signing off. The architects suspected the dampers were not actually required by code for this specific occupancy and assembly configuration, but confirming it the usual way meant setting up a meeting, a senior architect pulling code books, cross-referencing amendments, and chasing answers across the firm. On a project already under deadline pressure, the budget question was at risk of being closed out without ever being properly answered.
Instead, they ran the question through Ichi, an AI platform built specifically for navigating building code complexity. Within seconds they had a cited answer from the code confirming the dampers were not required. The line item came out. The client saved $250,000.
While this is a relatively small sum for highly complex projects, this is just a single example and without that quick verification, the money would not have stayed in the project. It would have come out of finishes, or contingency, or somewhere else the team would rather not have touched. That is the part worth paying attention to. Code research used to be a slow, senior-architect-only task that often gets skipped or rushed under deadline pressure. When it stops being slow, it starts shaping budgets in real time.
<h3 dir="ltr">How Manual Code Work Is Costing You</h3>
Code compliance is one of those parts of architectural practice that almost no one celebrates. It is also one of the most expensive parts of the job, in hours if not always in dollars.
Chinmayi Suri, an architectural designer at DGA, works on cGMP pharmaceutical, life science, and manufacturing facilities that often run past 100,000 square feet and carry layered regulatory requirements. She describes the existing process bluntly. Navigating ADA, fire codes, and industry-specific regulations falls on the most senior architects, the ones who have memorized chunks of code over years of repetition. It is institutional knowledge stored in human heads, queried one Slack message or in-person conversation at a time.
That creates two problems. The first is throughput. Senior staff become the bottleneck on every code question, which pulls them away from the design work they were hired to do. The second is timing. Code checking traditionally happens after the design is mostly finished, so compliance issues surface late, when changes are expensive and the schedule is already tight.
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"This stemmed from frustration really. I was sitting on my computer saying this should not take so long, and that's kind of actually where this all started."&nbsp;&mdash; Chinmayi Suri, DGA
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Her original interest in AI tools came out of that frustration, not out of any particular enthusiasm for AI as a concept.
<h3 dir="ltr">Why Generic AI Tools Fall Short</h3>
The obvious question for any architect frustrated with code research is: Can&rsquo;t ChatGPT do the job? The answer, so far, has been no, and the reasons are useful to understand.
Brandon Levey, founder and CEO of Ichi, comes from a 20-year tech background that includes work at a Department of Energy national lab and running R&amp;D teams at Square. He grew up in his father's HVAC and sheet metal business, which is partly why he ended up building software for AEC. He breaks the gap down into three things.
Accuracy on compliance codes has to be very high. Architects stamp their drawings, and a model that produces plausible-sounding language without citing the exact code section is worse than no answer at all. The documents themselves are also unusually large. A spec package can run 6,000 pages. A jurisdiction comment letter can run 60 pages with 300 individual items. General-purpose tools are not built to parse and cross-reference at that scale with any reliability. And, the answers always depend on the context that lives inside the firm: what counts as a standard detail, which assemblies the client has used before, what the senior architect on this project type would flag.
Chinmayi put it more directly. Generic AI tools require the user to already have deep domain knowledge to know what to ask and to verify what comes back. That defeats the purpose. The point of an AI assistant for code work is to lower the barrier, not require an expert to operate it.
<figure class="image"><img src="https://aecplustech-files.s3.amazonaws.com/blog/d43e9371-5c56-45b3-b46b-0264708472ca.png" alt="Ichi&rsquo;s agent based workflow helps teams organize code review, QA/QC, and consultant coordination tasks in a structured review board." width="1080"><canvas class="qb-highlighter__canvas" style="display: none; top: 1px !important; left: 200px !important;" width="47" height="22"></canvas>
<figcaption spellcheck="false" data-qb-tmp-id="lt-193248" data-gramm="false">Fig. 2) Ichi&rsquo;s agent based workflow helps teams organize code review, QA/QC, and consultant coordination tasks in a structured review board.</figcaption>
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<h3 dir="ltr">What Agentic Actually Means Here</h3>
Ichi's product is built around what Brandon calls an agentic approach. The term gets used loosely, so it is worth being specific.
In Ichi's case it means that when users ask Ichi a question they aren&rsquo;t interacting with a single LLM, but rather many different agents that are specialized in specific tasks. This approach helps the platform guide users when they do not know exactly what to ask,check its own work, and complete longer, more complex tasks.
A simple example. An architect asks a question about an auditorium in California. A generic chatbot returns a generic answer. Ichi instead asks clarifying questions about occupancy load and square footage, because those variables fundamentally change which code sections apply. That guided flow matters in code work, where a wrong assumption upstream invalidates everything downstream.
The error-checking piece is more technical but arguably more important.
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"Any type of long-running or long horizon task in AI is going to have errors in it. The way that we evolve through that, a lot of the agentic approaches are by using multiple AI agents to check its work."&nbsp;&mdash; Brandon Levey, founder and CEO, Ichi
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In practice that means when Ichi pulls code references from a 60-page comment letter or runs a feasibility study, separate agents are reviewing the output for inconsistencies and gaps before the architect sees it. That internal cross-check is what makes the difference between a curiosity and something architects will actually put their name on.
Want to hear the full discussion?<a href="https://www.youtube.com/watch?v=rsm_sSv2urI" target="_blank" rel="noopener"> Watch the complete panel conversation with Chinmayi Suri and Brandon Levey on YouTube.&nbsp;</a>
<h3 dir="ltr">Reducing the Work Architects Enjoy Least&nbsp;</h3>
The most concrete value Ichi delivers shows up in the workflows least enjoyed by architects.
Comment letters are the clearest case. When a jurisdiction returns a plan check, the architect's first job is translation: turning a long PDF into a structured spreadsheet that maps each comment to the relevant code reference, assigns it to the right consultant, and drafts an initial response. Brandon described one user who spent five to eight hours turning a 60-page letter with 300 comments into a workable spreadsheet. With Ichi, that drops to around 20 minutes.
Feasibility and zoning studies follow a similar pattern. A study that previously took two to four hours of senior staff time becomes a 20-minute guided workflow, producing an exportable document with code references already in place.
On the documentation side, the savings come less from automation than from triage. Chinmayi pointed to 700-page document sets where the real value is having AI do the first pass, locating where specific notes or drawing discrepancies live. The architect still verifies and decides. They just no longer have to read every line to find the three that matter.
The work that consumes the most time in an architecture firm is rarely the work that draws people into the profession. Cutting hours out of that work is where most firms will see the first real return.
<div><a href="https://www.youtube.com/watch?v=gSKu4e2Qg3s" target="_blank" rel="noopener">Watch Ichi in action: See how the platform supports zoning, design, permitting, and inspections across the full project lifecycle.</a></div>
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<h3 dir="ltr"><iframe style="display: table; margin-left: auto; margin-right: auto; width: 709px; height: 400px;" src="https://www.youtube.com/embed/gSKu4e2Qg3s" width="709" height="400" allowfullscreen="allowfullscreen"></iframe></h3>
<h3 dir="ltr">Capturing the Knowledge Before It Walks Out the Door</h3>
One of the more interesting features in Ichi is what the platform calls Memory. It captures the institutional knowledge of senior staff, the kind of judgment and pattern recognition that takes decades to build and tends to leave the firm when those people retire.
Chinmayi described how the idea took shape at DGA.
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"I wish we could put Mark Davis into a notebook LLM."&nbsp;&mdash; Chinmayi Suri, on DGA principal Mark Davis
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The line is partly a joke about a specific colleague, but it captures something the AEC industry has struggled with for a long time. Knowledge transfer from senior to junior staff is mostly accidental, dependent on proximity, mentorship, and time.
Memory works by ingesting organizational standards, past project notes, and client specifications so the AI's answers reflect the firm's actual way of working, not a generic best practice. DGA has started using it as a training tool, exposing younger architects not just to answers but to the prompts and reasoning senior staff use to get there. The platform already syncs directly with OneDrive and soon will with Google Drive, removing another friction point for firms with messy document storage.
This is also where the security question gets practical. Ichi does not train its models on customer data. For firms handling sensitive client information, particularly in life sciences or government work, that distinction is the difference between adoption and a hard no from legal.
<h3 dir="ltr">The Barriers Are Real, but Shrinking</h3>
Adoption is rarely about whether a tool works. It is about whether a firm can afford the time to find out.
Chinmayi named three barriers: time, trust, and security. Time, because evaluating new software is itself a senior-staff task that competes with billable work. Trust, because architects are personally liable for what they sign. Security, because client data cannot be pasted into a public chatbot.
The trust question tends to dissolve through small wins. Firms that successfully adopt AI usually start with a single project, often a smaller one, and prove the tool against a known answer. Once the output matches what a senior architect would have produced, the conversation shifts from whether the tool is reliable to which workflow it should touch next.
The fear of replacement also fades quickly once people actually use the tools. The intelligent part of the work, as Chinmayi pointed out, still comes from the humans using it. AI takes the repetitive parts. It does not make decisions, and it does not stamp drawings.
<h3 dir="ltr">The New Baseline</h3>
The shift Brandon describes has happened fast. In 2024, the conversation in architecture was still about whether AI was real. By late 2025 it had moved to how to implement it. Firms are now being asked in client interviews and RFP responses what their AI strategy is. Within the next year, not having a clear answer will start to count against firms competing for work.
Chinmayi frames it in the only terms that really matter to working architects.
<blockquote>
"You have to start using it. We have to start thinking about using it in our workflow. It is going to become as prevalent to us at some point as Revit is."&nbsp;&mdash; Chinmayi Suri, DGA
</blockquote>
The shift from hand drafting to CAD took roughly a decade. CAD to BIM took another. Each one looked optional at the start and obvious by the end. The shift now underway, from manual code research to agentic compliance tools, is following the same curve. 
Firms picking up the tools now are buying themselves time to figure out how to use them well before that becomes a job requirement rather than a competitive edge.
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<img src="https://aecplustech-files.s3.amazonaws.com/blog/1de0bf31-afe3-430b-82bc-a14f24bea959.png" alt="" width="160" height="160">
Editor's Note
This article is based on an aec+tech Expert Talk, Navigating Code Complexity with AI, featuring Chinmayi Suri of DGA Architects and Brandon Levey of Ichi. The conversation explored why building code review remains one of the most manual and time consuming parts of architectural practice, and how AI can help project teams navigate code requirements, reduce repetitive review work, and make more informed design decisions.
Learn more on Ichi&rsquo;s product page: <a href="../../tools/ichi" target="_blank" rel="noopener">https://www.aecplustech.com/tools/ichi</a>
Watch the full conversation here: <a href="https://www.youtube.com/watch?v=rsm_sSv2urI&amp;t=168s" target="_blank" rel="noopener">https://www.youtube.com/watch?v=rsm_sSv2urI&amp;t=168s</a>
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In this article, we explore how DGA Architects is using Ichi’s agentic AI platform to rethink building code compliance, QA/QC, and time consuming review workflows. Through a recent project example, the article shows how faster, cited code research helped the team remove a $250K fire damper line item and make better decisions earlier. The piece also looks at how AI can capture institutional knowledge, support junior teams, and become a new baseline for architecture firms as client expectations evolve.

How DGA Used Ichi’s Agentic AI to Rethink Code Compliance

<img src="https://aecplustech-files.s3.amazonaws.com/blog/57eee85d-cd2f-4ffd-842d-2e8a109ebfa4.jpg" alt="" width="1080">The difference between a concept and a market leader lies in the ecosystem in which they operate. If your startup is building the next generation of automation, artificial intelligence, or spatial intelligence for the built environment, this is your final opportunity to apply for the 2026 Trimble 0&ndash;60 Challenge. Applications officially close on May 22, 2026.
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Tech startups in the Architecture, Engineering, Construction, and Owner-Operator (AECO) sector often struggle to gain traction, not because they lack innovative ideas, but because they lack real-world domain context and access to established workflows. The Trimble 0&ndash;60 Challenge is a rigorous, equity-free 12-week sprint designed to help early-stage founders bridge the gap between digital concepts and physical workflows, moving solutions from prototype to real-world deployment.
<img src="https://aecplustech-files.s3.amazonaws.com/blog/b995bc3e-1078-4812-9fc9-3e86915c0297.jpg" alt="" width="1080">
Why This Accelerator Is Different
General-purpose accelerators can give you cloud infrastructure, but the Trimble 0&ndash;60 Challenge gives you the industry. Recently named the 2025 Accelerator Program of the Year by BuiltWorlds, this program provides what standard accelerators cannot: direct integration with the world's most widely deployed AECO platforms.
Startups selected for the 2026 cohort will receive:
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Deep Platform Integration: Build directly on Trimble Connect, SketchUp, Tekla, and ProjectSight, or integrate your computer vision and autonomy solutions with Trimble's GNSS receivers, total stations, and laser scanners.
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Expert Mentorship: Get weekly guidance from Trimble platform engineers, product teams, and Trimble Ventures advisors who have spent their careers inside construction workflows.
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Prizes and Market Distribution: Compete for non-dilutive cash prizes and gain a direct path to verified customers via a listing on the Trimble Marketplace.
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Demo Day at Dimensions: Pitch your fully functioning minimum viable product (MVP) to 5,000 construction professionals, buyers, and investors live at Trimble Dimensions in Las Vegas from November 9&ndash;11, 2026.
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Proven Commercial Outcomes
The 12-week roadmap focuses entirely on rapid development and commercial validation. As Simon Boyles, founder of ScaffPlan, noted after his cohort experience, "We finished the program with a brand new, fully functioning application ready to be commercialized". Similarly, the 2025 winner, Datagrid, successfully built an agentic AI tool that integrates directly with Trimble solutions and over 100 enterprise systems, which is now live on the Trimble Marketplace.
Who Should Apply
The program is actively seeking early-stage startups and developers building solutions in three core categories:
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Connected Data: Solutions that facilitate the seamless flow, management, and interoperability of data across the project lifecycle.
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Connected Design: Tools that enhance modeling, simulation, and design workflows to improve accuracy and efficiency.
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Connected Field or Jobsite: Technologies that optimize real-world execution through hardware-to-software synergy and precision technology.
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Key Dates for 2026:
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Applications Close: May 22, 2026
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Finalists Selected: June 12, 2026
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2-Day Kick-Off Event: June 16&ndash;17, 2026 (Westminster, CO)
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Dimensions Demo Day: November 9&ndash;11, 2026 (Las Vegas, NV)
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Do not watch the future of construction technology from the sidelines. If you are ready to scale your technology within the Trimble ecosystem, you must submit your application before the portal closes.
 Apply before midnight on May 22, 2026. <a href="https://www.trimble.com/en/our-company/events/dimensions/experiences/0-60-challenge?utm_source=influencer&amp;utm_medium=article&amp;utm_campaign=TRB-26Q1-GLOB-LE-Nov-09-Trimble-0-60&amp;utm_term=Aec+tech-campaign%20https://www.trimble.com/en/our-company/events/dimensions/experiences/0-60-challenge?utm_source=linkedin&amp;utm_medium=paid-ad&amp;utm_campaign=TRB-26Q1-GLOB-LE-Nov-09-Trimble-0-60&amp;utm_content=startups" target="_blank" rel="noopener">Learn more.</a></div>
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The 2026 Trimble 0–60 Challenge, an equity-free 12-week accelerator for early-stage AEC startups in automation, AI, and spatial intelligence, closes applications on May 22, 2026. Selected founders gain direct integration with Trimble platforms, expert mentorship, non-dilutive cash prizes, and a Demo Day slot at Trimble Dimensions in Las Vegas.

Last Call: Accelerate Your AEC Startup with the 2026 Trimble 0–60 Challenge

Graebert’s ARES Trinity 2027 helps AEC teams automate BIM-to-DWG documentation from Revit, IFC, and Autodesk Forma workflows. It reduces manual drawing updates, supports cloud automation, preserves CAD details, improves feedback loops, and introduces ARES Neo for Revit-based drawing validation.

BIM Has the Intelligence. Why Is Revit Documentation Still Manual?

Luminocity AG is a Swiss software-development agency headquartered in Schaffhausen with deep specialty in real-time 3D, AR/VR/XR, AI integration in 3D pipelines, and AEC plugin engineering. The agency operates as a hybrid services-plus-products company: alongside selective paid engagements with external customers, Luminocity ships several internal product lines that demonstrate the team's range across browser-native 3D, cloud BIM, and Gaussian-Splatting digital twins.

Product portfolio:

GeoVision is a cloud BIM visualization platform built on top of the Speckle data layer. Custom Revit and Archicad plugins (Rhino coming soon) move BIM models into a shareable web viewer where AEC teams collaborate, comment, and version on a single link without anyone needing Revit or Archicad installed. The plugin family captures PBR materials, lighting, and exposed metadata - notably above what stock Speckle connectors provide. A companion Unity 6 HDRP desktop application extends the workflow with immersive walkthrough and AI photorealistic image generation via the Grok (xAI) API. Live at geovision.cloud and app.geovision.cloud.

Lemonate is a complete open-source 3D game engine and editor that runs entirely in the browser - built ground-up by the Luminocity team. Lemonate features a LUA scripting layer for game logic; a full engine API across rendering, physics (rigid bodies, vehicle, NavMesh), positional audio, particle systems, materials and shaders; and a broad scene-object library including Gaussian Splats. Source code is public on Codeberg. A public games gallery, community asset library, and beginner / advanced tutorial series support the developer community. Lemonate has a public roadmap committed through 2027.

3D Replicas is a productized 3D Gaussian-Splatting digital-twin pipeline for cultural heritage, museums, and architectural sites. The three-stage workflow (on-site or studio capture, 3DGS reconstruction, cloud-delivered web / VR / archive output) has produced active client work in 2026 across multiple Italian heritage sites and Swiss commercial and civic spaces. Three productized offerings are available: Interactive Web Viewer, Virtual Museum Experience (VR/AR), and Digital Archive & Collection Management Platform.

Unity 3D consulting is the agency's bench-rental side: bespoke Unity3D engagements covering 3D content design, immersive experiences, custom rendering pipelines, and cross-platform deployment - on the same engineering bench that ships GeoVision's Unity 6 HDRP desktop application.

Our team's senior engineers carry more than 20 years of cumulative deep experience shipping advanced 3D systems with a cross-platform C++ core, integrated through Unity3D and browser-native runtimes. Past work includes industry-standard media servers used in some of the world's most demanding multimedia setups since 2007 (e.g. Eurovision Song Contests, large-scale 3D projection mappings, major touring productions), the MVX 2D / 3D / 4D file format and processing framework presented at Siggraph 2016, hardware-emulation work for leading VR device manufacturers, and a native Meta Quest VR application released in January 2026.

Engagement model:

Luminocity engages with external customers through a delivery-pod model. The customer describes what they need built and to what quality bar; the team handles execution internally (engineering, project management, QA all on the team's side); the customer receives working deliverables on the agreed cadence and integrates into their core stack. Engagements can be project-based or month-based, whichever fits the customer's pattern. Areas where the team is strongest: connector engineering for AEC plugins, custom AEC pipeline work on top of Speckle, front-end and viewer work in Three.js / WebGL / GLSL, AI integration in 3D pipelines, and Unity / AR/VR / XR engineering.

Headquartered in Schaffhausen, Switzerland; engineering team operates remotely across the EMEA region. English- and German-speaking. Tech stack includes C++, C#, JavaScript, TypeScript, Unity, Three.js, WebGL, OpenGL, OpenCV, AWS, Azure, Docker, Kubernetes, Terraform, Vue.js, React, Quasar, Node.js, and .NET.


Luminocity AG

Luminocity AG is a Swiss software-development agency in Schaffhausen specializing in real-time 3D, AR/VR/XR, AI integration, and AEC plugin engineering. Products include GeoVision (cloud BIM viewer), Lemonate (open-source browser-native 3D game engine), and 3D Replicas (productized 3D Gaussian-Splatting digital twins). 

InspectMind AI helps engineers review hundreds of pages of drawings in minutes instead of hours.
InspectMind AI is an AI-powered plan review and code compliance platform built for the architecture, engineering, and construction (AEC) industry. The platform automatically analyzes construction drawings, engineering plans, and technical documents to identify code violations, design inconsistencies, and constructability issues before projects move into permitting or construction.
Traditional plan review and QA processes require engineers, architects, and reviewers to manually analyze hundreds or thousands of pages of drawings. This process is time-consuming, expensive, and prone to human error. InspectMind AI accelerates this process by using advanced artificial intelligence models trained on construction drawings, building codes, and engineering standards.
Users upload their project plans directly to InspectMind, and the AI system analyzes the drawings sheet-by-sheet. The platform detects issues such as missing details, dimension conflicts, structural inconsistencies, accessibility violations, and code compliance risks. InspectMind then generates a structured report highlighting the detected issues along with visual references to the affected drawings.
The platform is designed for engineers, architects, developers, contractors, plan reviewers, and government agencies who want to reduce risk and improve design quality. By catching issues early in the design process, InspectMind helps teams avoid expensive rework, delays during permitting, and construction change orders.
InspectMind AI supports a wide range of building codes and standards including IBC, ADA, NFPA, and local jurisdictional codes. The system can analyze architectural drawings, structural plans, engineering reports, and construction documentation.
Typical workflow:
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Upload drawings Users upload their architectural or engineering plans directly into InspectMind.
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AI plan analysis The AI analyzes the full drawing set, identifies potential issues, and compares plans against applicable building codes.
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Review results Users receive a detailed issue report showing potential risks, code conflicts, and recommended corrections.
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InspectMind AI dramatically reduces manual review time, improves plan quality, and helps project teams move faster from design to construction.

InspectMind AI

Catch construction mistakes before they get built

AI-Powered Site Documentation: An InspectMIND Case Study

Featuring InspectMind AI at the AEC Innovate Conference

Featuring InspectMIND at the AEC Innovate Conference

Tools Leading the Way in the AEC+Tech Community

Using AI to Automate Building Inspections

Solibri CheckPoint is a browser-based BIM model checking platform that helps architecture, engineering, and construction teams improve model quality, coordination, and compliance&mdash;without heavy installs or steep training. Open a browser, review Revit and IFC models side by side, run standardized QA/QC checks (clash detection, data/property rules, clearances), and manage issues in one collaborative workspace that fits your existing CDE and project tools.
<h2 data-start="758" data-end="783">Why Solibri CheckPoint</h2>
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<li style="font-size: 15px;" data-start="784" data-end="888">Zero install, fast adoption: Web-based model checking reduces IT overhead and speeds onboarding.</li>
<li style="font-size: 15px;" data-start="889" data-end="985">Native Revit &amp; IFC support: Review the same source data&mdash;no exports or lossy conversions.</li>
<li style="font-size: 15px;" data-start="986" data-end="1090">Standardized QA/QC: Enforce modeling standards with reusable rule sets, filters, and data views.</li>
<li style="font-size: 15px;" data-start="1091" data-end="1208">Collaborative issue management: Assign, track, and resolve clashes/data issues with transparent audit trails.</li>
<li style="font-size: 15px;" data-start="1209" data-end="1370">CDE-friendly: Practical integrations with Autodesk Construction Cloud and Procore keep models and issues in sync via direct connections or BCF.</li>
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<h2 data-start="1372" data-end="1391">Key Capabilities</h2>
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<li style="font-size: 15px;" data-start="1392" data-end="1460">Clash detection &amp; constructability checks across disciplines</li>
<li style="font-size: 15px;" data-start="1461" data-end="1541">Property/data validation to enforce BIM standards and naming conventions</li>
<li style="font-size: 15px;" data-start="1542" data-end="1611">Clearance/free-space rules for safety, access, and operations</li>
<li style="font-size: 15px;" data-start="1612" data-end="1702">Data Viewer to inspect quantities, attributes, and patterns alongside the 3D model</li>
<li style="font-size: 15px;" data-start="1703" data-end="1804">Project Library to publish shared, repeatable templates (rules, filters, views) across projects</li>
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<h2 data-start="1806" data-end="1832">Integrations &amp; Workflow</h2>
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<li style="font-size: 15px;" data-start="1833" data-end="1939">Sync models and issues with Autodesk Construction Cloud and Procore (reduce duplicate uploads)</li>
<li style="font-size: 15px;" data-start="1940" data-end="2021">Export/import issues via BCF to keep coordination moving across platforms</li>
<li style="font-size: 15px;" data-start="2022" data-end="2138">Fit lightweight checks into more milestones&mdash;from schematic coordination to preconstruction and punch-list closeout</li>
</ul>
<h2 data-start="2140" data-end="2155">Who It&rsquo;s For</h2>
<ul data-start="2156" data-end="2394">
<li style="font-size: 15px;" data-start="2156" data-end="2237">Architects &amp; BIM Managers standardizing QA/QC and modeling best practices</li>
<li style="font-size: 15px;" data-start="2238" data-end="2319">General Contractors &amp; VDC Teams driving constructability and coordination</li>
<li style="font-size: 15px;" data-start="2320" data-end="2394">Owners/Consultants requiring transparent, auditable BIM deliverables</li>
</ul>
<h2 data-start="2396" data-end="2407">Benefits</h2>
<ul data-start="2408" data-end="2682">
<li style="font-size: 15px;" data-start="2408" data-end="2474">Higher BIM quality with consistent templates and rule sets</li>
<li style="font-size: 15px;" data-start="2475" data-end="2544">Fewer rework loops thanks to faster clash and data validation</li>
<li style="font-size: 15px;" data-start="2545" data-end="2608">Lower overhead via web-based access and simpler rollout</li>
<li style="font-size: 15px;" data-start="2609" data-end="2682">Better traceability with centralized issue records and auditability</li>
</ul>
Learn more: <a href="https://www.solibri.com/checkpoint?utm_campaign=3706145-Solibri%20CheckPoint&amp;utm_source=AEC%20Tech">www.solibri.com</a>

Model view IFC and Revit - Solibri CheckPoint

Solibri CheckPoint

Checking Revit models in the cloud with Solibri

Featuring Solibri at the AEC Innovate Conference

Solibri CheckPoint & the Future of AEC Model-Checking (2)

Acquisition of Xinaps and the rebranding of Verifi3D as Solibri Checkpoint

Solibri CheckPoint & the Future of AEC Model-Checking 

ARES Kudo: The Cloud-Based CAD Solution Empowered by AI In the rapidly evolving world of computer-aided design (CAD), ARES Kudo has emerged as a game-changing cloud-based solution. Developed by Berlin-based software company Graebert, ARES Kudo is the first online CAD software to reach feature parity with AutoCAD LT, making it a strong alternative for professionals looking for flexible and collaborative drafting tools. With its modern ribbon user interface and more than 300 CAD features, ARES Kudo enables seamless transitions from traditional CAD environments while introducing innovative cloud collaboration capabilities. One of the most significant recent advancements in ARES Kudo is the integration of artificial intelligence (AI). Graebert has introduced A3, an AI-powered assistant designed to enhance user experience, optimize workflows, and provide real-time guidance. Unlike generic AI chatbots, A3 is specifically trained in CAD applications, offering expert support tailored to users&rsquo; needs. A3: The AI-Powered CAD Assistant Artificial intelligence has become an integral part of daily life, from navigation apps to automated customer support. In the CAD industry, AI's potential is now being realized through tools like A3. Initially launched within ARES Commander, A3 is now fully integrated into ARES Kudo, bringing AI-driven assistance directly to users working in the cloud. A3&rsquo;s capabilities go beyond simple query responses. The AI assistant helps users locate commands within ARES Kudo&rsquo;s interface, provides step-by-step guidance on using features, and offers best practices for CAD design. For professionals transitioning from other platforms like AutoCAD, A3 simplifies the learning curve by instantly pointing out feature locations. For example, users can type &ldquo;Where is the PDF Import?&rdquo; and A3 will highlight the relevant tool within the interface. A3 also functions as an advanced knowledge source for CAD professionals, offering technical advice, design recommendations, and even industry-specific best practices. Whether users are looking for ways to streamline workflows or need assistance with a particular command, A3 serves as an on-demand expert. Beyond guidance, A3 can perform time-saving tasks such as unit conversions, text translations, and quick calculations. Its multilingual capabilities make it even more accessible, allowing users to communicate with the AI assistant in languages such as English, Spanish, French, German, and Japanese. Unlike traditional customer support, which may take hours or days to provide answers, A3 delivers instant responses, significantly improving productivity. A Cloud-Based Alternative to AutoCAD LT ARES Kudo&rsquo;s introduction of A3 is part of a broader effort to position itself as a leading online CAD platform. With a feature-rich environment and a familiar ribbon UI, ARES Kudo now matches AutoCAD LT&rsquo;s functionality while offering additional benefits unique to cloud-based solutions. One notable enhancement is its support for dynamic blocks, which ensures compatibility with AutoCAD files and facilitates seamless collaboration between different software environments. Additionally, the integration of the Trinity Block Library provides access to over 450 pre-built dynamic blocks, further boosting efficiency. By combining cloud accessibility with AI-driven support, ARES Kudo is redefining the CAD experience. Users can now enjoy a powerful, intelligent, and collaborative design environment, making ARES Kudo a compelling choice for professionals seeking innovation and efficiency in their CAD workflows. Learn more about the powerful solution here: https://graebert.pxf.io/JKJgyv

ARES Kudo now features an AI assistant with extensive CAD knowledge.

The ARES Trinity of CAD Software: Create and Modify DWG Files with Modern Collaboration Tools

ARES CAD Software: Top 10 Trinity Features Outperforming AutoCAD | Expert Review by Architosh

 Online CAD with Dynamic Blocks in ARES Kudo 

ARES Kudo: Full-featured 2D Online CAD for your DWG Drawings

ARES Kudo Online CAD for DWG Viewing, Creation and Modification in your Internet Browser

ARES Kudo

Cloud-Only Plan (includes ARES Kudo only)

Mobility Pack (includes ARES Kudo and ARES Touch)

ARES Trinity Plan (includes ARES Kudo, ARES Touch, and ARES Commander)

Because ARES Kudo runs in a browser, it can be accessed on any computer.

8600 AutoCAD users migrated to ARES CAD Software at Takenaka in Japan

Featuring Graebert at the AEC Innovate Conference

Featuring ArkDesign.AI at the AEC Innovate Conference

ARES Kudo: DWG Drawings Automation for Developers

ARES Kudo by Graebert Introduces AI to Assist Its Users

ArchiMind &mdash; Compliance Is No Longer Manual
For decades, California architects have done the same thing: finish the drawings, then spend days hunting through CBC chapters, marking up PDFs, and hoping nothing falls through the cracks before plan check.
ArchiMind ends that.
ArchiMind is a native Revit plugin that turns California building code into a live, intelligent layer inside your model. The moment you run an analysis, every room, door, stair, corridor, and restroom is evaluated against CBC 2025 &mdash; automatically, instantly, and without leaving Revit. No exports. No spreadsheets. No guesswork.
<hr>
Built for the Code That Actually Governs California Projects
California doesn't run on IBC.
ArchiMind was built from the ground up for this stack:
<ul>
<li style="color: #000000;">CBC 2025 + 2022 &mdash; both editions, data-driven, always current</li>
<li style="color: #000000;">CPC 2025 Table 422.1 &mdash; exact stepped fixture counts by occupancy, not simplified ratios</li>
<li style="color: #000000;">Chapter 11B &mdash; the strictest accessibility standard in the country, fully implemented</li>
<li style="color: #000000;">DSA IR 10-2 + IR 11B-10 &mdash; K&ndash;12 and state-funded project requirements that other tools skip entirely</li>
</ul>
This isn't a multi-jurisdiction platform retrofitted for California. This is California, done right.
<hr>
12 Domains. One Click. Everything Checked.
ArchiMind evaluates your model across every major CBC review category in a single run:
Occupancy Load &middot; Egress &middot; Stairs &amp; Ramps &middot; Fire Resistance &middot; Height &amp; Area &middot; Light &amp; Ventilation &middot; Chapter 11B Accessibility &middot; Restroom Fixtures &middot; Plumbing Fixture Count &middot; EVCS Parking &middot; Exit Signs &middot; DSA Path of Travel
Every result is tied to a specific Revit element and cited to the exact code section. Not "something might be wrong." Exactly what, exactly where, exactly why.
<hr>
Not Just Flagging &mdash; Fixing
Most compliance tools stop at flagging. ArchiMind goes further.
Click GoTo on any failing check &mdash; Revit zooms directly to the element. Click Fix &mdash; ArchiMind corrects it automatically. Door too narrow? Fixed. Handrail too low? Fixed. Ramp too steep? Fixed. Stair too narrow? Fixed. Corridor too tight? Fixed. Every fix is fully undoable with Ctrl+Z. Re-run the analysis to confirm.
Click What's Checked in the dashboard to see every check ArchiMind runs, which ones have auto-fix available, and what's on the roadmap &mdash; full transparency, no black box.
For corridor and stair width violations, the Guide Lines tool draws red dimension annotations directly on your floor plan &mdash; showing exactly how far a wall needs to move. For restrooms, blue annotation boxes appear next to each room showing required vs. provided fixture counts from CPC Table 422.1, plus CBC 11B ADA clear floor area calculations.
This is the difference between a report that tells you what's wrong and a tool that helps you fix it.
<hr>
Compliance That Runs While You Design
ArchiMind's Live mode monitors your model continuously in the background. The moment a room change triggers an egress violation or a door swap creates a width issue, you know &mdash; while it's still a 30-second fix, not a 3-day redesign.
<hr>
For the Whole Team
<ul>
<li style="color: #000000;">Architects &amp; designers &mdash; catch issues during design, not at plan check</li>
<li style="color: #000000;">BIM managers &mdash; embed compliance into your standard Revit QA workflow</li>
<li style="color: #000000;">Project managers &mdash; track compliance status across every active project from the team dashboard, no BIM file required</li>
<li style="color: #000000;">Plan check consultants &mdash; pre-check before DSA or city submission and cut review cycles in half</li>
</ul>
<hr>
The Numbers
200+ compliance checks &middot; 12 CBC domains &middot; 4 California code layers &middot; Revit 2023&ndash;2026 &middot; CBC 2022 &amp; 2025 &middot; CPC 2025 &middot; Chapter 11B &middot; DSA IR 10-2 First CBC run free. No credit card required.

ArchiMind

ArchiBoost AI is an AI-powered co-pilot built specifically for the Architecture, Engineering, and Construction (AEC) industry. Developed by architects and engineers rather than generic AI developers, the platform helps project teams navigate complex building regulations, activate institutional knowledge, and automatically review project documentation to identify coordination risks and compliance issues before they become costly problems.
ArchiBoost AI supports architects, engineers, developers, and general contractors working across the full project lifecycle&mdash;from early design through construction documentation and project delivery.
The platform combines three core capabilities into a unified intelligence system: Code Compliance, Knowledge Hub, and AI-powered QA/QC review.
1. Code Compliance &mdash; Project-Aware Regulatory Intelligence
ArchiBoost provides project-specific code compliance guidance, not just code search.
The system evaluates project conditions&mdash;including occupancy classification, construction type, fire separation distance, and jurisdiction&mdash;to determine the exact requirements that apply to a project. It automatically resolves the hierarchy between international, state, and municipal codes, ensuring that teams see the governing regulations rather than conflicting sources.
Each response includes clear explanations and direct citations to the applicable code sections, helping teams confidently apply requirements during design, documentation, and plan review.
By identifying compliance paths early, ArchiBoost helps teams avoid costly redesigns, permit delays, and late-stage documentation changes.
2.1. Knowledge Hub &mdash; Institutional Intelligence for AEC Firms
Architecture firms often possess vast amounts of knowledge scattered across project folders, standards manuals, specifications, and internal documentation. ArchiBoost transforms this information into a structured and searchable intelligence layer.
The Knowledge Hub organizes two key knowledge domains:
Firm Intelligence &ndash; reusable internal standards such as BIM execution plans, QA/QC checklists, documentation standards, master specifications, and lessons learned from previous projects.
Project Intelligence &ndash; project-specific information such as owner standards, design guidelines, specifications, schedules, meeting minutes, and consultant documentation.
This structure allows teams to quickly access relevant information without manually searching through large document repositories.
2.2 Detail Library &mdash; A Living Library of Proven Solutions
Within the Knowledge Hub, ArchiBoost includes a Detail Library that transforms past project details into a living, searchable resource.
The platform extracts metadata from drawing sets and organizes details based on parameters such as: - project type - construction type - occupancy classification - applicable codes - jurisdiction - client standards
Teams can quickly locate vetted details from previous projects and reuse them with confidence. The system integrates directly with Revit, allowing teams to insert editable details into their models without interrupting their design workflow.
This helps firms standardize documentation, preserve institutional knowledge, and reduce time spent recreating common solutions.
3. AI-Powered QA/QC Review
ArchiBoost automatically analyzes complete drawing sets&mdash;including architectural and consultant documentation&mdash;to identify coordination gaps, inconsistencies, scope omissions, and potential compliance risks.
Issues are surfaced through a structured ticketing system that links directly to the relevant sheet location. Teams can review findings, assign ownership, track resolution, and export issue reports for consultant coordination.
By identifying problems earlier in the documentation process, ArchiBoost helps reduce RFIs, change orders, and costly rework during construction.
Who Uses ArchiBoost AI
ArchiBoost AI is designed for: - Architecture firms working across multiple jurisdictions - Design teams producing large, multi-disciplinary drawing sets - Developers seeking early compliance validation - General contractors reviewing documentation prior to construction - Firms looking to activate and scale institutional knowledge across projects and offices
Platform Overview
ArchiBoost AI is delivered as a cloud-based SaaS platform that integrates with existing AEC workflows and documentation processes.
By combining regulatory intelligence, institutional knowledge, and automated QA/QC review in one platform, ArchiBoost enables teams to identify risks earlier, make better design decisions, and deliver higher-quality projects with fewer surprises.

ArchiBoost AI

CRDR BIM, short for "Clash Resolution Diagnosis Report in BIM," is a specialized tool designed to streamline clash resolution documentation within Autodesk Navisworks. It simplifies compliance reporting and enhances workflow efficiency for BIM managers, coordinators, and specialists by providing a structured approach to documenting resolved clashes. 1. Efficient Clash Resolution Reporting CRDR BIM enables users to generate detailed Clash Resolution Diagnosis Reports that document how clashes have been addressed between different BIM model versions. This feature helps teams maintain accurate records of resolution progress, improving project tracking and compliance. 2. Seamless Navisworks Plugin Integration Functioning as a dedicated Navisworks plugin, CRDR BIM integrates directly into existing workflows, allowing users to compare &lsquo;before&rsquo; and &lsquo;after&rsquo; BIM models effortlessly. This integration ensures that clash resolution documentation remains within the familiar Navisworks environment, eliminating the need for external tools. 3. Intuitive &amp; User-Friendly Interface Designed for ease of use, CRDR BIM features an intuitive interface that simplifies navigation and workflow execution. BIM professionals can efficiently document and categorize clashes without technical complexity, improving productivity and adoption rates. 4. Consistent Viewing Angles for Clear Comparisons CRDR BIM ensures consistent perspective when capturing images of clashes, maintaining uniformity between different model versions. This feature enhances clarity in reports, making it easier for teams to analyze and understand clash resolutions. 5. Customizable Clash Categorization for Precise Documentation Users can categorize clashes into resolved, unresolved, approved, or resolved but connected manually, ensuring a clear and organized approach to documentation. This categorization allows for better project tracking and compliance verification. 6. Flexible Reporting Formats for Easy Sharing CRDR BIM supports HTML and PDF export options, enabling teams to save and share reports efficiently. These reports include detailed images and summaries, making them valuable for project documentation and stakeholder communication. 7. Enhancing BIM Management with Streamlined Reporting By integrating directly with Navisworks, CRDR BIM empowers BIM managers and specialists to document clash resolutions accurately and efficiently. It ensures that compliance reporting is effortless while maintaining a structured and transparent workflow. With its powerful reporting features and seamless integration, CRDR BIM is an essential tool for professionals involved in clash resolution documentation within BIM models.

CRDR BIM

Melt Takeoff is built for estimators who need takeoffs that are not just fast, but truly bid-ready and reliable. Unlike fully automated takeoff software that only measures what&rsquo;s drawn, Melt Takeoff is designed around a simple truth: winning bids requires accounting for what&rsquo;s missing from plans &mdash; the scope gaps, incomplete details, coordination conflicts, and implied work that experienced estimators catch through judgment.
Melt Takeoff combines AI vision with expert estimator validation to deliver takeoffs with both speed and accuracy. The workflow is simple: upload plans, the AI measures and identifies scope, flags drawing/spec conflicts, adds allowances, and then senior estimators validate everything before delivery. This hybrid model is what makes Melt Takeoff dependable &mdash; AI accelerates measurement, but real estimators ensure completeness and constructability.
Key capabilities include:
<ul data-start="923" data-end="1834">
<li data-start="923" data-end="1042">
AI Vision measurement detecting 800+ building elements with counts, lengths, perimeters, areas, and volumes
</li>
<li data-start="1043" data-end="1129">
Automated scope recognition across architectural, structural, and MEP drawings
</li>
<li data-start="1130" data-end="1256">
Detailed allowances for scope not shown, added as itemized ROMs based on code requirements and real project benchmarks
</li>
<li data-start="1257" data-end="1351">
Drawing&ndash;spec conflict detection, with estimator-led resolution before it hits your bid
</li>
<li data-start="1352" data-end="1528">
Estimator-verified outputs, reviewed by onshore senior estimators with 20+ years of field experience, including delivery of multi-million to billion-dollar projects
</li>
<li data-start="1529" data-end="1691">
Flexible classification standards, supporting MasterFormat&reg;, UniFormat&reg;, or custom structures, so takeoffs drop directly into your estimating workflow
</li>
<li data-start="1692" data-end="1834">
Interactive takeoff output, with side-by-side plan review, traceable quantities, and clean Excel exports ready for pricing and bidding
</li>
</ul>
Melt Takeoff is designed for speed without sacrificing trust. Quantities aren&rsquo;t just dumped into a spreadsheet &mdash; they&rsquo;re delivered in a structured, reviewable format so teams can validate quickly, collaborate internally, and confidently move into bid submission. The output stays fully in your control: review, adjust, and export clean files without messy reformatting.
Melt Takeoff delivers a takeoff process that is 40% more accurate, 20% faster, and 10% cheaper, with turnaround times ranging from 2&ndash;3 days for small projects to 7&ndash;8 days for extra-large projects. The result is fewer missed scope items, stronger bid coverage, reduced risk of underbidding, and significantly more confidence in your numbers &mdash; so estimators can bid faster and win more work.

Melt Takeoff

Reer is&nbsp;an Intelligent Design Environment that brings AI directly into&nbsp;Rhino (&amp;Grasshopper), Revit, and more.
While most AI tools in AEC work on downstream point solutions like documentation, compliance, and visualization, Reer works upstream, directly at the source, the CAD and BIM model files where every project decision originates.
For decades, CAD and BIM platforms have been the backbone of AEC projects worldwide. They are powerful, deeply embedded, and not going anywhere. But the way professionals interact with them has barely changed. Most tasks remain manual, repetitive, and error-prone, requiring users to translate their intent into commands, scripts, and step-by-step operations rather than focusing on the work that actually requires their expertise.
Reer brings a true CAD-native AI collaborator directly into the tools we all rely on, fundamentally changing that interaction. The agent understands the context of your model, acts on your behalf, and handles the full range of workflows professionals deal with every day:
<ul class="[li_&amp;]:mb-0 [li_&amp;]:mt-1 [li_&amp;]:gap-1 [&amp;:not(:last-child)_ul]:pb-1 [&amp;:not(:last-child)_ol]:pb-1 list-disc flex flex-col gap-1 pl-8 mb-3">
<li class="whitespace-normal break-words pl-2">Batch edits and parametric modeling</li>
<li class="whitespace-normal break-words pl-2">Data extraction and analysis</li>
<li class="whitespace-normal break-words pl-2">Object, layer, and file organization</li>
<li class="whitespace-normal break-words pl-2">Cross-platform coordination</li>
<li class="whitespace-normal break-words pl-2">Visualization and rendering</li>
<li class="whitespace-normal break-words pl-2">Construction documentation</li>
<li class="whitespace-normal break-words pl-2" style="font-style: italic;">And more for you to explore...</li>
</ul>
Beyond individual productivity, teams can build custom skills and modules on top of Reer, turning everyday interactions into reusable design intelligence that compounds over time.
The long-term vision is one intelligent environment across the entire AEC project lifecycle, from schematic design in Rhino through coordination in Revit and beyond.
Reer is currently in Free Beta in Rhino - <a class="underline underline underline-offset-2 decoration-1 decoration-current/40 hover:decoration-current focus:decoration-current" href="https://www.food4rhino.com/en/app/reer-ai">Try it now</a>
Revit coming in June!

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