<div><img src="https://aecplustech-files.s3.amazonaws.com/blog/5741b41d-2b98-40f9-9a96-00550e6d0a57.png" alt="InspectMind AI" width="1080"></div>
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<div>Most conversations about AI in construction start with speed.&nbsp;</div>
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<div>&ldquo;How many hours did we save?&rdquo;</div>
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<div>&ldquo;How many pages could we review in minutes?"&nbsp;</div>
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<div>But a recent aec+tech conversation on AI-driven plan review made a more useful point: the tools save time, but the real reason to adopt them is risk.</div>
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<a href="https://www.youtube.com/watch?v=r0nEGFxC7as">This conversation</a> brought together Colton Johnson, Principal Engineer at Flint Engineering Company; Aakash Prasad, Co-founder and CEO of InspectMind AI; and Simon G. Solorio, President of Solorio Inc. Much of the discussion centered on InspectMind AI's plan-checking tool, though the takeaways apply to any firm weighing this kind of software.&nbsp;
In this article you&rsquo;ll see where AI plan review helps, where it falls short, and why a firm with weak internal processes will not get much out of it no matter how good the software gets.
<h2 dir="ltr">Reading a Pictorial Language</h2>
Plan review is not just about reading text. Construction documents carry meaning through symbols, callouts, line weights, and schedules that change from one project type to the next. An industrial set does not look like a large residential set. Every new hire has to learn how to read that visual system before they can review anything in it.
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"Construction documents are a language, and on top of that they're a pictorial language. You're relying on graphic and visual cues to display the information, translating heavy analysis and code requirements into those pictures."
&mdash; Colton Johnson, Principal Engineer, Flint Engineering Company
</blockquote>
Solorio described the second half of the problem: volume.&nbsp;
Even with tools like Revit and virtual walk-throughs on Meta Quest headsets, engineers still check ever-changing building codes by hand and coordinate across disciplines. Holding hundreds of pages of drawings against dense architectural, structural, mechanical, and civil specifications is a cognitive load that does not scale. There is only so much one person can keep straight at once, and plan sets keep getting bigger.
That is the gap AI steps into. Not the design work or the engineering judgment, but the slow, repetitive cross-checking that wears people down and still lets errors slip through.
A Third-Party Reviewer That Works Through Lunch
<figure class="image"><img src="https://aecplustech-files.s3.amazonaws.com/blog/bb52d8a0-3272-45e5-b6a9-e96e1717194f.png" alt="Errors missed in review surface on site, where fixes cost most." width="1080">
<figcaption spellcheck="false" data-qb-tmp-id="lt-8150" data-gramm="false">Fig 2) Errors missed in review surface on site, where fixes cost most.&nbsp;</figcaption>
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AI is a third-party reviewer. It&rsquo;s not a replacement for the engineer or the plan checker, but an extra set of eyes that never gets tired and never skips a page.
Prasad said InspectMind AI can typically review a 100- to 200-page project in one to two hours. In that window it catches discrepancies between drawings and specs, flags cross-discipline coordination issues, and checks against selected/applicable codes and references. It surfaces a prioritized set of findings while the team continues other work.&nbsp;
InspectMind AI has flagged a water main running straight into a 12-inch concrete pipe. It has caught a storm sewer drawn with no slope, which means it would never drain. These are the errors that hide on page 140 of a set and get expensive once they reach the field.&nbsp;
<blockquote>
"This isn't replacing your own diligence or your own quality of work. It's a useful automated review tool that helps you reduce risk and liability and improve quality overall."
&mdash; Aakash Prasad, Co-founder and CEO, InspectMind AI&nbsp;
</blockquote>
The discussion was honest about the limits, too. AI still struggles to read the purely graphical parts of a drawing when there are no words or numbers to anchor it. That should improve over the next few years, but for now InspectMind AI is strongest where drawings, specs, and code references can be grounded and cited. Purely graphical meaning, where the intent lives only in the picture, is still an area where human review matters.
<h2 dir="ltr">From Months of Back-and-Forth to Days&nbsp;</h2>
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<figure class="image"><img src="https://aecplustech-files.s3.amazonaws.com/blog/c6175af5-f771-4066-a384-2d4991e7ce06.png" alt="InspectMind AI tags each finding by severity, discipline, and code." width="1080">
<figcaption>Fig 3) InspectMind AI tags each finding by severity, discipline, and code.&nbsp;</figcaption>
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A minor discrepancy on a drawing is not just a quality problem. It is a liability problem. Prasad pointed to ADA compliance as an example. A ramp drawn with a 2.2 percent slope instead of the required 2 percent maximum is a small number on a sheet and a frequent target for litigation. Catching it before construction starts is worth far more than the hour it saved.
The same logic runs downstream. Errors that survive review become Requests for Information (RFIs) and change orders once contractors are on site. Each one costs time and money and strains the client relationship. The financial case lives in catching those errors early.&nbsp;
A church project in California shows how that plays out. The design firm ran its full drawing set (architecture, civil, structural, and specs) through InspectMind AI before submitting to the city. The AI flagged around 300 issues. The team fixed them first. When the city's review came back, the comments were mostly minor, and the firm closed them out in days rather than the weeks or months a project like this can take.
That is the payoff that matters. Not the hours saved running the review, but the weeks of back-and-forth with the jurisdiction that never happened, and the rework that never reached the field.
Garbage In, Garbage Out Still Applies
<figure class="image"><img src="https://aecplustech-files.s3.amazonaws.com/blog/88271371-af97-4945-8f3f-0a5ee2295ce9.png" alt="AI only reflects the inputs it gets." width="1080">
<figcaption spellcheck="false" data-qb-tmp-id="lt-415377" data-gramm="false">Fig 4) AI only reflects the inputs it gets.</figcaption>
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The strongest warning has always been against leaning on the tools too hard. The old 'garbage in, garbage out' rule still stands.
The software is powerful, but it sits on top of a firm's inputs, its standards, and the judgment of the people running it.
Solorio made the case for foundational knowledge. Junior engineers still need to learn the basics through hand calculations and free-body diagrams so they understand how loads travel and what a structural member is actually doing. Without that, an engineer cannot tell when the AI is wrong.
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"If you put in garbage, you're going to get out garbage, and that's still true with these new programs. If you put in something wrong, it gives you something wrong. You have to know the basics to know when it's giving you wrong information."
&mdash; Simon G. Solorio, President, Solorio Inc.
</blockquote>
Johnson framed the same idea as a sequence. He sees a working AI workflow as a three-tier system.&nbsp;
A firm establishes good internal processes first. Then it introduces standard automations. Only then does it put AI at what he called the tip of the spear. Skip the first two steps and there is nothing solid for the AI to stand on. When a firm's drawing standards and inputs are inconsistent, there is no realistic way to scale an AI workflow on top of them.
<h2 dir="ltr">Own the Output</h2>
Accountability is the other side of this. When an engineer signs off on a design, they own it, whatever tools helped produce it.
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"The motto we live by with AI is own the output. Just because you have a cool tool doesn't mean you get to say that the tool is the reason something was wrong. You own the output."
&mdash; Colton Johnson, Principal Engineer, Flint Engineering Company
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That has a practical edge. Johnson raised data security, pointing out that client information needs to stay protected under NDAs when a firm runs it through a third-party AI platform. Owning the output means owning the data path, too. Before uploading project documents, firms should evaluate the data path and the platform's NDA and security requirements. That is a question to settle before the first project goes up, not after.&nbsp;
<h2 dir="ltr">Built by the People Who Use It</h2>
The panel closed on what actually makes these tools better, and the answer was feedback from the field rather than anything happening in a lab. Solorio and Johnson both pointed to the value of a simple thumbs up or thumbs down on each flagged issue. That input teaches the model the difference between a real problem and an irrelevant false positive, which is the difference between a tool engineers trust and one they learn to ignore.
Because AEC technology moves quickly, the tools that respond to this feedback can change almost daily. Johnson offered an example from a job site. He floated the idea of having the plan checker automatically generate a targeted field observation checklist based on the specific materials and structural elements it found in the drawings. Within hours, the development team had piloted a connection between the plan checker and a site inspection app.
That speed of iteration is the point underneath the whole conversation.
The AI plan review tools that earn a place in AEC workflows will be the ones built and shaped by the people doing the work, not the ones that promise to do the thinking for them. The engineers on this panel were not looking for software to replace their judgment. They were looking for a reviewer that helps them protect it. That is a smaller promise than replacing an engineer, and a far more useful one.
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To learn more about InspectMind AI, visit InspectMind AI's <a href="../../../tools/inspectmind-ai" target="_blank" rel="noopener">page on aec+tech </a>or explore the latest features and request access on the InspectMind AI's <a class="_ymio1r31 _ypr0glyw _zcxs1o36 _mizu194a _1ah3dkaa _ra3xnqa1 _128mdkaa _1cvmnqa1 _4davt94y _4bfu18uv _1hms8stv _ajmmnqa1 _vchhusvi _kqswh2mm _ect4ttxp _syaz13af _1a3b18uv _4fpr8stv _5goinqa1 _f8pj13af _9oik18uv _1bnxglyw _jf4cnqa1 _30l313af _1nrm18uv _c2waglyw _1iohnqa1 _9h8h12zz _10531ra0 _1ien1ra0 _n0fx1ra0 _1vhv17z1" title="https://www.inspectmind.ai/" href="https://www.inspectmind.ai/" target="_blank" rel="noopener" data-renderer-mark="true" data-is-router-link="false" data-testid="link-with-safety">website</a>.
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Editor's Note
<img src="https://aecplustech-files.s3.amazonaws.com/blog/c3806924-0521-483d-b74d-a01f09ed330e.png" alt="Niknaz Aftahi" width="160" height="160">
This article was independently reviewed and edited by Niknaz Aftahi, Founder of AEC+Tech, drawing on InspectMind AI's product documentation, direct conversation with the panel participants, and hands-on knowledge of plan review and QA/QC workflows. Figures drawn from the panel rather than published material were checked before publishing.
&mdash; Niknaz Aftahi, Founder, AEC+Tech
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</div>

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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.
<blockquote>
"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="What Agentic Actually Means Here" 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.
<blockquote>
"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
</blockquote>
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.
<blockquote>
"I wish we could put Mark Davis into a notebook LLM."&nbsp;&mdash; Chinmayi Suri, on DGA principal Mark Davis
</blockquote>
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="niknaz aftahi" 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

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The Context
Despite decades of investment in BIM, architectural documentation remains heavily manual. Teams continue to spend significant time on repetitive production tasks, manual QA/QC, and enforcing standards across drawings, views, and schedules.
At scale, this creates inefficiency, late-stage rework, and coordination risk, while contributing to burnout across documentation teams. Existing automation is often fragmented or difficult to apply consistently within live project models, limiting its effectiveness in everyday production work.
SketchPro is being actively deployed at top architecture firms to address this gap by embedding AI directly into architectural documentation workflows.
The Question
How can AI support architectural documentation&ndash; QA/QC, standards alignment, and repetitive production work&ndash; while keeping architects in control, preserving authorship, and respecting firm-specific standards and workflows?
The Approach
SketchPro is an AI documentation copilot embedded directly within Revit, designed to operate on live project models, views, schedules, and sheets. The system is developed around three core principles:
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No workflow disruption Al actions occur inside the same Revit environment already used by project teams for documentation. No exporting, syncing, or parallel tools required.
</li>
<li dir="ltr" aria-level="1">
Architect-in-the-loop control All actions are previewed, reviewable, and reversible, ensuring professional judgment remains central to decision-making.
</li>
<li dir="ltr" aria-level="1">
Firm-specific intelligence Rather than applying generic rules, the system adapts to project standards, naming conventions, and documentation logic defined by each practice with an &ldquo;AI Knowledge Base&rdquo; set up by admins from each firm.
</li>
</ul>
The Collaboration Model
SketchPro is being deployed in collaboration with architecture firms working across a range of scales, typologies, and geographic locations, including educational, multifamily, and commercial projects. Ongoing collaboration ensures the platform addresses real documentation pain points such as QA/QC consistency, annotation cleanup, and standards alignment within live projects.
The Results
Across partner firms, teams report:
<ul>
<li dir="ltr" aria-level="1">
Standardized preferences across projects with AI
</li>
<li dir="ltr" aria-level="1">
30% reduction in documentation time across major tasks like sheet creation, dimensioning, schedules, and QA/QC
</li>
<li dir="ltr" aria-level="1">
20% more capacity to do more projects with their current team
</li>
</ul>
AI is experienced as a support system rather than a replacement. Junior staff report increased confidence and productivity, while senior staff retain full control over technical decisions.
Key Takeaways
Successful AI adoption in architecture depends less on automation alone and more on customization, transparency, and trust in the technology.
By embedding AI directly into documentation workflows and aligning it with the realities of architectural practice, SketchPro illustrates how AI can strengthen existing processes rather than disrupt them, supporting efficiency, quality, and professional judgment.

SketchPro allows you to go from a hand-drawn sketch to a fully rendered design

Firm-specific intelligence based on a custom, internal knowledge base

Mentor mode provides model-specific guidance

QAQC Audit using your firm's standards and checklists

SketchPro.ai

MeltBid by MeltPlan is an AI bid leveling software built for general contractors in preconstruction. The traditional bid leveling process takes estimators hours of manual work &mdash; pulling numbers from PDFs, building spreadsheets by hand, hunting for buried exclusions, and hoping nothing slips through before you award. MeltBid compresses all of that into minutes.
The workflow is straightforward: upload your subcontractor proposals and MeltBid automatically structures them into a leveled comparison inside your own Excel template or a provided one. It works both in the browser and natively inside Excel via MeltPlan's Microsoft marketplace add-in, so estimators don't have to change how they work.
The value, though, goes well beyond speed. MeltBid surfaces five core capabilities:
Bid leveling in minutes. Upload multiple proposals &mdash; PDFs from each sub &mdash; and get a fully populated line-by-line comparison in your template in under 5 minutes. Bring your own format or start from MeltBid's.
Scope gap detection. Automatically identifies line items that one sub priced and others excluded or missed entirely. These gaps are the silent killers in preconstruction &mdash; they show up as change orders in the field, well after you've already awarded the contract.
Exclusions and qualifications flagging. Highlights non-obvious exclusions and qualifications buried deep in bid packages &mdash; things like "fire alarm devices excluded," "roof penetrations not included," or "price valid 30 days only, subject to material escalation." The cheapest number on paper becomes the most expensive one post-award when these get missed.
Full traceability. Every number in the leveled output links directly back to the source line in the original proposal. No black box &mdash; estimators can click any cell and see exactly which clause in which sub's PDF drove that value, with a "Mark as Reviewed" workflow to systematically work through the output.
Natural-language AI Q&amp;A. Ask plain-English questions directly against your leveled bids: "Who is the lowest bidder and by how much?" "What did Summit exclude?" "Where's the biggest spread across bidders on mechanical?" MeltBid answers in context, scoped to the exact run you're reviewing.
It's built for the way estimators actually work &mdash; in the browser or right inside Excel &mdash; and is aimed squarely at GCs who are tired of the bid leveling process eating their preconstruction capacity.

Melt Bid

Ichi is an AI-powered code compliance and automation platform built for architecture firms.
The platform helps architects navigate complex building codes, automate time-consuming construction administration tasks, and strengthen QA/QC across the entire project lifecycle&mdash;from early design through construction.
Designed specifically for the realities of architectural practice, Ichi augments professional expertise by automating previously manual processes, improving accuracy, and minimizing costly downstream rework. The platform supports both project-level execution and firm-wide knowledge sharing, helping teams work more efficiently while maintaining accountability and control.
Key Features
<ul>
<li dir="ltr">AI Code Compliance Reviews</li>
</ul>
Ichi enables architects to quickly search, interpret, and validate applicable building codes and jurisdictional requirements. AI-assisted guidance is presented alongside authoritative source language, allowing teams to confidently apply code requirements during design, documentation, and review&mdash;without relying on generic or unverified AI outputs.
<ul>
<li dir="ltr">Automated Construction Administration</li>
</ul>
The platform helps automate and support manual construction administration workflows, including navigating construction documents, responding to RFIs, and reviewing submittals. By reducing the time spent on repetitive coordination tasks, Ichi helps keep projects moving while easing the administrative burden on architectural teams.
<ul>
<li dir="ltr">QA/QC at Scale</li>
</ul>
Ichi strengthens QA/QC by assisting with plan set reviews, cross-sheet consistency checks, and document validation across large and complex drawing packages. This allows architects to identify issues earlier, improve document quality, and reduce risk prior to submission or construction.
<ul>
<li dir="ltr" style="font-weight: bold;">Institutional Knowledge Management</li>
</ul>
Ichi acts as a living knowledge base for architecture firms. Project-specific decisions, jurisdictional nuances, and internal best practices can be captured, shared, and reused across teams and over time&mdash;helping firms preserve institutional knowledge as staff, projects, and regulations change.
Who Should Use Ichi?
Ichi is designed for:
<ul>
<li dir="ltr" style="font-size: 14px; font-family: helvetica, arial, sans-serif;" aria-level="1">
Architecture firms working across multiple jurisdictions
</li>
<li dir="ltr" style="font-size: 14px; font-family: helvetica, arial, sans-serif;" aria-level="1">
Design teams navigating complex or evolving code requirements
</li>
<li dir="ltr" style="font-size: 14px; font-family: helvetica, arial, sans-serif;" aria-level="1">
Firms seeking to reduce QA/QC risk and rework
</li>
<li dir="ltr" style="font-size: 14px; font-family: helvetica, arial, sans-serif;" aria-level="1">
Architects managing heavy construction administration workloads
</li>
<li dir="ltr" style="font-size: 14px; font-family: helvetica, arial, sans-serif;" aria-level="1">
Practices looking to capture and scale internal expertise
</li>
</ul>
While built with architects at the center, Ichi also supports collaboration with engineers and contractors by improving clarity, consistency, and access to critical project information.
Why Ichi?
Ichi is purpose-built for the architectural profession. Unlike general-purpose AI tools, it is designed to operate within the constraints of real-world practice&mdash;prioritizing accuracy, traceability, and professional responsibility.
By combining AI-driven code compliance, QA/QC automation, construction administration support, and firm-wide knowledge management in a single platform, Ichi helps architects spend less time on rote tasks and more time on high-value design and decision-making. The result is better documentation, smoother project delivery, and more resilient architectural practices.
Learn More
Ichi is helping architecture firms modernize how they manage code compliance, QA/QC, and knowledge across their projects, all on one platform.
👉 Visit https://www.ichiplan.com/ to schedule a demo or learn more about how Ichi is helping architects and other AECs build cities of the future.

Ichi

We lead the construction industry in quality control. No more stumbling blocks. Constructing flawless buildings is now easier than ever. Solibri Office imports building models from all major BIM software using the standardized IFC interface. It identifies potential problems early, preventing issues during construction and beyond, ensuring smooth project execution and long-term building performance. Solibri offers the most advanced and comprehensive library of customizable rule templates to tackle the most demanding quality assurance tasks. Choose from over 70+ predefined rule templates or customize your own to ensure no stone is left unturned. Go beyond clash detection and take your BIM quality to the next level. Solibri offers a wider range of checking capabilities than any other tool in the market: geometry, clearance, accessibility, information &amp; property checking, building code compliance, model revision, fire safety and more. Solibri understands your role and offers you a set of rules, classifications, and reporting templates that you can customize to match your company, project, local, or national needs. Use organizational tools like classifications and filters to streamline model checking, to takeoff quantities and data, or to visualize the BIM data/components in the model. Information takeoff allows you to extract quantities based on different criteria more easily. Share the information using your own customized Excel templates. Information takeoff allows you to extract quantities based on different criteria more easily. Share the information using your own customized Excel templates. Share project information and collaborate seamlessly and reliably through Solibri&rsquo;s integrations, BCF Live Connector and API. Automate tasks, such as running checks, exporting the identified issues as BCF files and creating presentations, and run them at a convenient time with Solibri Autorun. Easily integrate with your workflows: Solibri is founded on openBIM standards to foster interoperability and enable transparent, open cooperation among all project participants. This allows model authors and collaborators to connect Solibri's quality assurance capabilities with the tools of their choice.

Solibri Office

Eight categories reveal how AEC technology evolved on aec+tech.

Building Better with BIM QA: 2025 Interview with Solibri

Checking Revit Models in the Cloud with Solibri

Featuring Solibri at the AEC Innovate Conference

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

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>
<ul data-start="784" data-end="1370">
<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>
</ul>
<h2 data-start="1372" data-end="1391">Key Capabilities</h2>
<ul data-start="1392" data-end="1804">
<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>
</ul>
<h2 data-start="1806" data-end="1832">Integrations &amp; Workflow</h2>
<ul data-start="1833" data-end="2138">
<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

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 

Melt Code is the first building code research AI built for accuracy, transparency, and real compliance decision-making. Unlike generic AI tools that behave like black boxes, Melt Code doesn&rsquo;t just provide an answer &mdash; it shows the full research process so architects and engineers can verify every step and confidently defend their decisions.
Users can ask code questions in plain English and receive reliable, project-specific requirements with:
<ul data-start="804" data-end="1586">
<li data-start="804" data-end="857">
Step-by-step reasoning with clear assumptions
</li>
<li data-start="858" data-end="927">
Direct citations to exact code sections for full traceability
</li>
<li data-start="928" data-end="1139">
Compliance Paths, mapping multiple valid routes to compliance (based on occupancy, construction type, sprinkler conditions, height/area limits, ratings, etc.) so teams can choose the best design approach
</li>
<li data-start="1140" data-end="1242">
Exception and cross-reference handling, including circular references across multiple chapters
</li>
<li data-start="1243" data-end="1343">
Table and diagram understanding, ensuring accurate interpretation of code tables and figures
</li>
<li data-start="1344" data-end="1450">
Built-in calculations, such as occupant loads, egress sizing, travel distances, and fixture counts
</li>
<li data-start="1451" data-end="1586">
Personalized compliance illustrations, automatically generated to visually explain requirements for a specific project scenario
</li>
</ul>
Beyond research, Melt Code includes workflow tools that turn compliance into an organizational asset:
<ul data-start="1692" data-end="1990">
<li data-start="1692" data-end="1858">
Projects, where teams store project context (location, occupancy, construction type, sprinkler status, etc.) so every question becomes instantly project-aware
</li>
<li data-start="1859" data-end="1990">
Checklists, allowing firms to build, store, share, and export reusable compliance checklists across teams and project types
</li>
</ul>
The result is dramatically faster research, fewer senior escalations, reduced consultant dependence &mdash; and most importantly, confidence and peace of mind in every code decision.

Melt Code

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

Discover how the Kusch Consulting engineering team streamlined their structural engineering projects, saving up to 20% in time using ClearCalcs.

Kusch Consulting is a structural engineering firm based in Australia that specialises in residential, commercial, and industrial projects. With a team of 32 engineers spread across Melbourne, Sydney, Brisbane, and Adelaide, they handle a wide range of projects, from one-story residential homes to power station upgrades.

Richard Faulkner, Senior Structural Engineer at Kusch Consulting, first heard about ClearCalcs from another engineer who recommended it as an alternative to his existing software. Since then, Richard has introduced it to his team at Kusch Consulting, and over time, it has become an essential part of the team’s workflow. 

From quickly estimating beam sizes during initial project discussions to generating detailed reports during the design phase, ClearCalcs has made every step of the process easier and faster for Richard and his team.

A typical structural design project for an engineer like Richard begins with initial discussions with architects or clients to understand the project requirements. Richard often uses ClearCalcs early in this process for preliminary sizing and feasibility assessments. Once a project moves into the design phase, Richard uses ClearCalcs for detailed load analyses, calculations, and report generation.

Kusch Consulting x ClearCalcs

ClearCalcs is changing how the world is built with a platform that gives engineers and designers everything they need to streamline engineering design calculations. Built by engineers, and trusted by thousands, ClearCalcs’ comprehensive calculator library makes it easy to design to your local codes and standards. Our revolutionary drag and drop calculator builder and API enables anyone from a solo engineer to a product manufacturer to create, share, and automate everything from a single spreadsheet, all the way to a full engineering application.

ClearCalcs

Discover how SMARTBuild Engineering is leading sustainable building and social housing design with a forward-thinking approach.

SMARTBuild Engineering x ClearCalcs

The Challenge: Increased Data Required for Design of More Resilient Structures

An increasing number of Aurecon’s clients are following lessons learned from the Canterbury Earthquakes. They are requesting resilient structures in order to facilitate post-earthquake operations of their businesses.

In response, Aurecon designs buildings that employ the most effective known seismic mitigation technologies such as sliding hinge joints for low damage connections and Ringfeder friction springs that cushion seismic vibrations. These technologies allow a building to move during a seismic event with a minimum amount of damage to the building’s structural and architectural elements.

Data Grows in Volume and Complexity

Aurecon Sliding Hinge JointClinton Maulder, Associate – Buildings, Aurecon has needed a way to get data from an engineering spreadsheet into the Revit model without having to transfer it over manually. In one project, just one of many elements, sliding hinge joints – nine or 10 different ones – had to be tabulated. Standard detail tables had to be compiled. Engineering loads needed to be input into piling schedules; plate, bolt, and pre-stressing configurations for Ringfeder connections needed to be tabulated.

Conclusion

In addition to using Ideate BIMLink for this seismic work, it has also recently been implemented to coordinate sheet and drafting information across (65) emergency response service departments, with the work being done by Aurecon’s engineers at three different New Zealand locations. In the words of Clinton Maulder, “It worked a treat, with 65 emergency response facilities ready for people to populate and we didn’t have to worry about naming consistency, because Ideate BIMLink had taken care of it.”

According to Clinton, “Being able to effectively deal with source data and eliminate ‘double handling’ saved time and reduced the chance of errors. Ideate BIMLink is structured to leave a lot to the individual’s imagination. It is hard to come up with a finite list of things it can do.”

Read the full case study at: https://ideatesoftware.com/about/customer-success/spotlight-on-aurecon

Streamlining Seismic Mitigation Work with Ideate BIMLink

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Why choose Ideate BIMLink?
Linking Revit and Excel with Ideate BIMLink enables you to export data from Revit to Excel, streamlining data management tasks and dramatically reducing the time they take to perform. By creating a bidirectional connection between the model and a spreadsheet environment, teams can extract large volumes of element data, edit parameters in bulk, validate information, and apply changes using Excel&rsquo;s powerful sorting, filtering, and formula tools. This eliminates the need to manually open and edit individual elements in Revit, significantly reducing repetitive work and the risk of human error.
Importing data from Excel back into Revit means that your models are instantly updated with approved changes, helping ensure they remain clean, coordinated, and accurate. Ideate BIMLink provides access to nearly all instance and type parameters, including many that are difficult to manage efficiently using native Revit schedules alone. This expanded access gives teams greater control over project data, improves consistency across models, supports internal standards, simplifies model auditing, and strengthens overall data governance practices. It also enables collaboration with stakeholders who may not work directly in Revit but can safely contribute through structured Excel-based workflows.
Boost the Power of Ideate BIMLink with Ideate Automation
Add Ideate Automation to your subscription* to reduce the cost of repetitive BIM tasks by letting them run in the background while your staff focuses on higher-value work. This scripting solution can be run manually or scheduled to operate at convenient times, providing just-in-time insight into key Revit model metrics while automating essential workflows such as:
Producing document issue records Exporting PDFs Exporting health check data Preparing COBie data drops Generating quantity takeoff data
By automating these recurring processes, teams improve efficiency, strengthen data accuracy, increase consistency, reduce risk, and deliver more predictable project outcomes without interrupting daily production workflows across projects.
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Ideate BIMLink - Overview on Data Management

Ideate BIMLink

Australia

You&rsquo;ve mastered creativity, solved client challenges, delivered great work yet somehow value just keeps slipping away. Not because you&rsquo;re bad at what you do, but because the system you&rsquo;re working in was never built to support&nbsp;you.
The remedy is not in better design. It&rsquo;s in&nbsp;better systems.
Meet bugleViewer an operating system for protecting your value and accelerating cash flow. We know design consultants lose thousands chasing clients and unpaid work &mdash; so we built a system that puts you back in control of your IP and your cash flow!
So how will bugleViewer help you may ask? The answer &mdash; it&rsquo;s like having a lawyer, a project manager and a collections agent, all working silently in the background.
<ul>
<li data-start="814" data-end="936">Want your next contract approved without the never-ending back and forth? Expedite the execution of your next contract all inside bugleViewer.</li>
<li data-start="814" data-end="936">Want to keep project momentum alive? Use bugleViewer's one click sign-off workflow and forgo the cumbersome email trail.</li>
<li data-start="814" data-end="936">Want to keep your IP safe during feedback loops? Take advantage of our secure document viewing technology and keep your work visible (not vulnerable).&nbsp;</li>
<li data-start="814" data-end="936">Want to keep everyone accountable for what they said? Centralise your communications inside bugleViewer and give every decision, comment and approval a home.</li>
</ul>
When you deploy bugleViewer into your business, you leave behind the old cycle: the endless chasing, the mis-communication and the frustration that builds on both sides of the client-consultant relationship when value starts to leak.&nbsp;&nbsp;
Curious to see what the future of your practice could look and feel like?
Claim <a style="color: #ee6002;" title="The Modern Professional's Edge Offer" href="https://buglelabs.com/get-started" target="_blank" rel="noopener">The Modern Professional's Edge Offer</a>&nbsp;and see first hand how to turn client back-and-forth into confident project leadership (the kind that boosts your reputation, project morale and your bottom line).
If you&rsquo;ve been waiting for a system that works for you, not against you, then this is your moment.
Give us just 30 days &mdash; and we&rsquo;ll show you how well your projects could run forever.
If you're not ready just yet to claim your edge, why not see how your existing client systems stack up and where bugleViewer could help you modernise and streamline your process. <a href="https://buglelabs.com/take-the-quiz">Take the 2 minute Modern Practice Scorecard</a>.&nbsp;
Every business owner deserves systems that protect what they create. You built your business to design &mdash; not to chase clients, approvals and unpaid invoices.
You already know how to design. Now design a business that works just as beautifully.
Claim your edge with bugleViewer.&nbsp;

bugleViewer

We’re creating a calculation management platform to bring engineering teams, design and data together. Traditional engineers play a vital role in society. They build the infrastructure we depend on a daily basis, from roads, cars, to hospitals, schools and our homes. Problem: 40% of an engineers’ time is spent searching through past projects, rebuilding calculations and wrangling data. Solution: CalcTree no/low code platform takes away a lot of the manual steps, freeing up engineers to create more innovative and sustainable designs.

CalcTree

Archistar creates cutting-edge technology that revolutionises the way property professionals plan, design, build, and sell. We are an award-winning, fast-growing PropTech start-up with a smart, fun team. We are investor-backed and are bringing to market exciting SaaS products: 🏢 Archistar: Discover new opportunities and unlock the potential of a portfolio within minutes. Learn more: www.archistar.ai 🏡 Archistar Homes: Sell more homes using visually striking, user-friendly tools that increase transparency for both home buyers and home sellers. Learn more: www.archistar.ai/for-home-builders 🏘️ Snaploader: Bring your projects to life and maximise your sales opportunities with interactive 3D experiences for real estate. Learn more: www.archistar.ai/snaploader 🏫 Archistar Academy (formerly IDDA): Rapid online learning for the AEC industry. Whether you’re a student or an experienced professional, we have the online training you need. Learn more: https://academy.archistar.ai/ Our team is agile and full of A-players. We hire star performers and are eager for new team members to help us grow and scale up.

Archistar

SkyCiv provides engineers powerful and easy-to-use structural analysis and design software - all on the cloud. No downloading or installing, it's as simple as login from a web browser, anytime, anywhere. In a few simple clicks you can have instant access to powerful Structural Analysis and Design Software that can handle: - 3D Structures including beams, frames, plates and cables - Full Section Builder for custom shapes, built-up sections and US, UK, Aus and Canadian libraries - AISC and other design code checks - Powerful PDF reporting with custom logos With all this included in a single subscription, you can handle any structures that come your way!

SkyCiv

Best for individuals assessing the software

Basic: Best for individuals or short term projects

Professional: Best for medium-large companies with specific needs

Enterprise: Best for medium-large companies with specific needs

Result for “Australia”

Companies "2 results"

DIRT

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