The first of these is neural CAD, an AI model that’s trained to reason about CAD objects, according to Autodesk.

“Moving far beyond the practice of pairing large language models with existing solutions, Autodesk’s approach completely reimagines the traditional software engines that create CAD geometry or translate between industrial and architectural systems,” wrote Autodesk’s Mike Haley, leader of the machine intelligence group at Autodesk Research, in a blog post yesterday.

Autodesk announced two types of neural CAD that will soon be available for Forma and Fusion users. Forma, Autodesk’s AEC platform, will get neural CAD for buildings. Haley wrote that it “enables customers to quickly transition between early design concepts and more detailed building layouts and systems.”

In Fusion, neural CAD for geometry “is an entirely new, machine learning approach to generating CAD objects in contrast to the classical parametric CAD engines employed for over 40 years,” according to Haley. Neural CAD will allow users to generate, via text prompts, boundary representation (BREP) geometry that can be edited within Fusion.

Autodesk is also expanding its chatbot, Autodesk Assistant, in both functionality and availability. It will be available across Autodesk products including Fusion, Vault, Revit and more. In a press briefing last week, Haley described Autodesk Assistant as a “thought partner” for design and manufacturing.

One new feature that Autodesk is bringing to the Assistant is the ability for users to generate photorealistic, context-aware renderings of their Fusion designs. In his blog post, Jeff Kinder, executive vice president of product development and manufacturing solutions at Autodesk, gave the example of an air fryer being rendered in  a kitchen environment.

The rendering feature comes through a collaboration with Microsoft by which Fusion can tap into Microsoft AI services like Azure OpenAI. The resulting renders can “then be exported to Microsoft 365 and converted to a Microsoft PowerPoint presentation, eliminating the need for users to manually produce creative collateral,” Kinder wrote.

Engineering.com is live at Autodesk University in Nashville this week. Stay tuned and subscribe for further updates.

The post Autodesk introduces “neural CAD” at AU 2025 appeared first on Engineering.com.

Today’s top story: EDA developer Cadence has announced it will acquire Hexagon’s design and engineering business, including the assets of MSC Software, for approximately €2.7 billion (US$3.17 billion) in a mixture of cash and stock.

With this acquisition, Cadence can expand its structural simulation portfolio, which began last year with the $1.24 billion acquisition of developer Beta CAE. The company’s ultimate goal is to offer a unified multiphysics simulation platform encompassing electromagnetics, electrothermal, CFD and structural analysis.

“By adding Hexagon’s D&E [design and engineering] world-class simulation capabilities, we will expand our vision of Intelligent System Design to encompass the full spectrum of physical behavior—from electromagnetics and fluids to structures and motion. This will be a pivotal step in enabling our customers to design the complex, converged systems of tomorrow,” said Cadence CEO Anirudh Devgan in the company’s press release.

For Cadence, the juiciest morsels of this deal are probably those from the erstwhile MSC Software, which Hexagon acquired in 2017 for $834 million. Cadence’s announcement specifically calls out Nastran, MSC’s well-known FEA solver, and Adams, its multibody dynamics simulation software.

What else is Cadence getting in the deal? According to Hexagon’s press release: “The D&E perimeter includes MSC (acquired in 2017) and subsequent acquisitions including AMendate (2019), Romax (2020), CADLM (2020) and CAEfatigue (2020).”

Cadence expects to finalize the acquisition in the first quarter of 2026, with the usual regulatory caveats.

New version of Artec Studio adds automation to 3D scan processing

3D scanning company Artec 3D has released the latest version of its scanning software, Artec Studio 20.

One highlight of the new release is the ability to create custom automation pipelines, called Workflows, that Artec says will make data processing up to 70% faster.

“Ideal for repeat tasks, all-new Workflows eliminate human error, improve process repeatability, and deliver high-quality results users can rely on. For even greater automation, those with an annual subscription can use scripting to set up workflows that import, process, and export data to third-party software. This integration allows for batch processing, saves users from sitting at their PCs, and unlocks further opportunities for accelerating the processing of similar datasets via fully autonomous file transfer,” according to Artec 3D’s announcement.

Artec Studio 20 also adds new capabilities to several of the company’s 3D scanners, such as the Artec Spider II, Artec Micro II, Artec Point, and Artec Leo. I reviewed the Leo back when it launched in 2021, using Artec Studio 15 to process my scans. It was a more laborious process than I expected, so I imagine that the new automation capabilities will be most welcome for anyone doing it regularly.

CloudNC releases CAM Assist 2.0

CloudNC has released CAM Assist 2.0, an update to its web-based CAM automation platform.

Like Toolpath and Siemens NX CAM Copilot (not its real name), CAM Assist uses AI to automatically create machining toolpaths. It supports 3-axis and 3+2 operations and integrates with Autodesk Fusion, Siemens NX, and Mastercam.

The 2.0 update “combines the speed of AI-powered toolpath generation with new step‑by‑step oversight, giving programmers even greater control,” according to CloudNC.

This video from CloudNC shows the platform in action:

Alongside the new release, CloudNC also announced that CAM Assist is being used by over 1,000 machine shops globally. If you’re one of them, let me know your thoughts on the platform at malba@wtwhmedia.com.

Register for Digital Transformation Week 2025

Starting September 22, 2025, Engineering.com will host a week of webinars all about Digital Transformation. We gave it the most creative name we could think of: Digital Transformation Week 2025.

“A few years ago, most companies approached digital transformation as a hardware issue. But those days are gone,” writes Engineering.com senior editor Michael Ouellette. “Now the conversation is a strategic one, centered on data management and creating value from the data all the latest technology generates. The onrush of AI-based technologies only clouds the matter further.”

Join Michael and his special industry guests for the series of webinars by registering here.

One last link

How do you make a world without landmines? Engineering, of course. Design World Editor-in-Chief Rachael Pasini explores a fascinating solution in Eagle A7 prevents landmine casualties with drone-mounted AI.

Engineering Paper will be blank next week. See you in two Tuesdays.

Got news, tips, comments, or complaints? Send them my way: malba@wtwhmedia.com.

The post Cadence to buy Hexagon’s design and engineering business for $3.17 billion appeared first on Engineering.com.

This episode of Industry Insights & Trends is brought to you by Siemens.

Engineering design is an iterative process. It’s been said that engineering is not about design, but redesign, and the stepwise pathway toward verified, proved in production ready parts and assemblies is frequently restrained by testing and validation.

But what if the design tools can themselves flag the designer about trouble very early in the design process? It’s a “shift left” in the design timeline, and it represents a way to build better, faster and with less risk. Advanced engineering software tools such as Siemens NX Performance Predictor deliver these benefits without the need to extensively retrain design personnel.

***
Learn more: engineering.com is hosting Design Like a Pro: The Power of Simulation in Your Workflow webinar on Monday, September 29, 2025. Registration and attendance is free.

The post From idea to impact: Accelerating the engineering workflows appeared first on Engineering.com.

… Is what I’d normally say, but software news has been slow this Labor Day pre-kend, weekend, and week-in. Which gives me a perfect opportunity to cover something I’ve been meaning to write about for months, and you’ve been meaning to read about for just as long (though you didn’t know it).

AI is coming to Siemens NX X Manufacturing (again)

Back in July I was in Detroit for Realize Live 2025, Siemens’ annual user conference. I covered the highlights at the time, but I didn’t get around to an interview that I had with Siemens’ Michael Taesch, senior director of product management, and Sashko Kurciski, marketing director for digital manufacturing, about AI for NX CAM.

“We’re trying to see how we fuse AI into our manufacturing process,” Taesch told me.

One result of that fusion is an upcoming AI tool that generates machining strategies for NX users. It’s not available yet and it doesn’t have an official name, but for the sake of conversation Taesch and Kurciski called it the CAM Copilot within NX X Manufacturing. For the sake of this article, I’m going to call it NX CAM Copilot.

With a couple clicks, NX CAM Copilot—not its official name—will generate three possible ways to machine a given feature (and more if needed). The user can take these as a starting point to develop their program. The AI will debut with 2.5 and 3-axis machining strategies and expand from there.

“We’re not here to replace the manufacturing engineer,” Taesch said. “We want to give him multiple processes, and it’s up to him to pick the right one based on his knowledge.”

With a familiar thumbs up/down system, users will be able to rate the suggestions and, in theory, the AI will learn their preferences and improve over time.

“Manufacturing is complex,” Kurciski said. “You can machine a single feature in—I’m not exaggerating—10 different ways with 15 different tools. So you have your own company best practices, and capturing this is very important.”

In that sense, Siemens sees NX CAM Copilot—again, not its official name—as a tool for knowledge capture, one that can help bridge that engineering skills gap that technology vendors keep talking about.

“Company A will program their way. Company B will have a completely different process,” Taesch added. “You cannot have a generic solution. You need to have something that’s tailored, personalized to the customers.”

But the more direct utility of NX CAM Copilot is in its efficiency. Like anything, CAM programming takes time, even for the experts.

“Though I’ve been 10 years in NX CAM, I always make mistakes when I start the programming,” Taesch said. “Here, in a couple clicks, I get a result, and then all I have to do is just fine tune, use my knowledge to adjust a little bit.”

Taesch estimates that NX CAM Copilot can save 80% or more of the time that users would otherwise spend on CAM programming. “I can quickly program a part. Might not be perfect, but if I wanted to quickly quote it, in five minutes I can get something up and running,” he said.

NX CAM Copilot is currently in beta, but Taesch said Siemens plans to release it by the end of 2025. Taesch expects the AI tool to be an add-on to NX X Manufacturing through Siemens’ value-based licensing program, though that isn’t a final decision. (There’s an extant NX X Manufacturing copilot, which is just a chatbot, that’s currently available as a value-based add-on. Perhaps this new tool will be integrated into that.)

NX CAM Copilot, which is a placeholder name, reminds me of Toolpath, which sounds like a placeholder name but isn’t. Toolpath is a web-based platform that uses AI to generate toolpaths (and as I covered last week, it just announced Autodesk as an investor). I brought up the comparison to Taesch and Kurciski, who offered the opinion that Toolpath is more of a black box solution focused on quoting, while NX CAM Copilot provides more tailored manufacturing choices.

“We have another project that is working in parallel where we automatically ingest for quoting,” Taesch added. “It’s going to be tied into NX CAM. And the idea will be to leverage this tool to provide some simple quotes. Not there yet, but we have it in mind.”

So there you have it—an AI engineering tool from Siemens that’s a lot more interesting than Design Copilot NX. I’ll bring you more on NX CAM Copilot, or whatever it will be called, as soon as I learn it (or several months later, whichever comes first).

One last link

Ever wonder what’s inside a 1950s Heathkit vacuum tube oscilloscope? EE World’s Martin Rowe reveals all in his latest teardown—but he needs your help to put it all together.

Got news, tips, comments, or complaints? Send them my way: malba@wtwhmedia.com.

The post Siemens NX is getting an AI copilot for CAM appeared first on Engineering.com.

Green energy initiatives are pushed out every year by companies in a variety of different industries and markets. While the concept of a “green initiative” is appealing on the surface, many companies relegate their environmentalism to a single line or moonshot project. CEE was founded on the idea that they wanted to be a clean tech supplier with a clear goal of pushing down CO2 emissions in energy intensive production processes.

While so many companies are founded on these green principles, CEE is looking to both talk the talk and walk the walk. Ray and Jules coffee was launched by CEE to be a centerpiece for the company to showcase what they can achieve with green technology and engineering, and demonstrate how it is not only possible, but also successful. 

“I’m a clean tech entrepreneur, and I have a formation as an engineer. My brother is an engineer; my father is an engineer. My father’s father is an engineer. So, we have a serious problem in the family,” jokes Koen Bosmans, CEE’s founder and CEO.

But all joking aside, it’s apparent that Bosmans is serious about green tech. He channels this generational expertise into transformative industrial solutions, aligning environmental sustainability with economic practicality.

CEE distinguishes itself through vertical integration, combining consulting, engineering and manufacturing under one roof. Unlike traditional firms specializing exclusively in one market, CEE’s approach allows a comprehensive and seamless service, enhancing the efficiency and feasibility of delivering complex technological innovations.

“Let’s say you have consulting companies, you have engineering companies, you have manufacturing companies,” Bosmans says. “And we decided, okay, let’s push all of this together under one umbrella in our niche of thermal treatment systems, energy efficiency, industrial energy efficiency. And voila! That’s what I’ve been doing the last 18 years.”

Engineering Meets Coffee

In 2014, CEE recognized a critical inefficiency in the roasting of bulk food products. Conventional methods relied heavily on batch roasting processes, characterized by high temperatures and significant energy consumption. Identifying an opportunity for meaningful impact, CEE developed a continuous roasting system that operated at lower temperatures and achieved significantly better energy conversion rates.

Like many established organizations, traditional industrial coffee roasters have a tendency to be extremely risk-averse, which means avoiding being an early adopter to new tech — especially when that tech requires capital investment or an overt shift in processes.

“Those big companies, they don’t like to take big risks in their eyes. In our eyes, it was not a big risk. It was like a calculated risk and one step at a time. Lots of tests and then a first pilot, and then a second pilot, and then the industrial scale. But those big established companies, let’s say they are risk averse and sitting on existing assets. They only move if they see it work elsewhere first, and that’s actually what we created. We created our own first reference for a certain technology ourselves,” Bosmans explains.

Determined to prove the viability of their technology and spread the influence of their energy-efficient opportunity, Bosmans and his team took the bold step of creating a sister company, Ray and Jules, in 2017 to prove the technology’s commercial viability. Ray and Jules became the world’s first zero-emission coffee roastery, exclusively powered by renewable energy and utilizing CEE’s innovative roasting system.

By acquiring an existing small coffee roastery, CEE combined their advanced technological knowledge with practical roasting expertise, bridging the gap between innovation and market acceptance. Over two years, they developed a fully operational facility, launching publicly in December 2019. Ray and Jules quickly gained traction, growing into a prominent brand in Belgium, now serving over 35,000 customers and clearly demonstrating consumer demand for sustainable alternatives.

Ray and Jules’ success provided a critical proof-of-concept, drawing attention from global leaders in the coffee, cocoa and malt industries. Companies previously cautious about adopting new technologies were now keen to explore the potential benefits. CEE strategically invited these industry giants to conduct tests with their own raw materials at Ray and Jules’ facility, providing tangible evidence of the technology’s effectiveness. This approach significantly lowered perceived risks, gradually fostering acceptance and adoption of CEE’s innovations within traditionally conservative industries.

“That’s what was needed to make them shift a little bit. That’s how Ray and Jules actually became part of the CEE group, and now it’s a well-known coffee brand in Belgium with a large number of clients,” Bosmans says.

Evidence-Based Engineering with the Help of Simulation

Central to CEE’s engineering process is their strategic deployment of Siemens’ Solid Edge software, part of the Designcenter suite, and their offering of 3D modeling, simulation and analysis capabilities. CEE has a need to create precise and meticulous designs, which is crucial for efficient and accurate on-site implementation. Nuts, bolts, washers and detailed assembly marks are added into the design, ensuring that installations proceed smoothly, rapidly and with minimal disruption to existing operations.

Solid Edge’s simulation capabilities, particularly in computational fluid dynamics (CFD), play a crucial role in CEE’s design process. By using Simcenter FLOEFD to perform CFD simulations, the company’s engineers are able to precisely analyze and optimize thermal interactions within roasting and drying systems, ensuring uniform heat distribution and consistent product quality. This detailed simulation and iterative refinement drastically reduce both technical and financial risks associated with scaling innovative industrial processes from laboratory concepts to full commercial operations. Arguably, it is a big part of the success that the Ray and Jules coffee company has achieved.

Additionally, CEE uses what Bosmans has coined as an evidence-based engineering approach, complementing Solid Edge simulations with rigorous laboratory testing. By collecting precise, empirical data from small-scale tests, engineers can benefit from holistic and data-rich digital twins provided through the Siemens Xcelerator software suite.

“You always need to put numbers, magic numbers, into the model. Since you’re not always certain about the product’s chemical composition. That’s where the tests come up,” Bosmans explains. “We say, let’s take the product of the client. Let’s put it in a certain thermal atmosphere and measure how it reacts. How fast does it heat up in a certain environment? How fast does it start to evaporate the liquid inside? And then we combine the two. That’s where the magic happens — because of course, we can’t run tests at full scale; it would be far too expensive. Instead, we conduct small-scale tests and use that data as input for the model. From there, we can scale the model up to full size. Evidence-based engineering is critical for us. We’re very good at collecting precise measurements and using them to feed our digital twins.”

This synergy between empirical evidence and advanced modeling significantly reduces uncertainty and accelerates the transition from prototype to production scale.

Critical Engineering for Coffee

CEE’s innovative reach extends beyond food processing into the construction materials sector, as well. Despite the apparent differences between these industries, both require sophisticated thermal management. CEE’s cross-sector expertise enables them to transfer insights and technological advancements seamlessly between different industries, continually driving innovation and efficiency improvements.

Looking to the future, CEE remains committed to broadening its global impact. Recognizing the limitations of regional markets, the company has proactively expanded its operational presence to North America, aiming to effectively serve its growing global client base. CEE’s strategic decision to focus deeply within their niche expertise rather than broadly diversifying their services ensures sustained specialization, innovation and competitive advantage.

“If you want to grow, you should go abroad. Because we are a Belgium-based company now, I cannot sell 50 dryers per year in Belgium. That’s impossible. The market is much too small. So then the question is, do we expand our services? Or do we say, no, we want to stay the specialist in our niche? We have clearly chosen this second option. But the result is then that we need to follow the clients wherever they go,” says Bosmans.

“That’s exactly what we’re doing right now. Our customers are pushing us to expand our expertise — and I think that’s a good thing. There’s nothing better than smart clients; they challenge you to reach the highest possible level.”

Ultimately, CEE’s mission goes beyond mere technological advancements. It embodies a vision where environmental sustainability and economic success are mutually reinforcing goals. By continuously pushing technological boundaries and leveraging tools like Solid Edge and embedded Simcenter FLOEFD, CEE provides a compelling example of how engineering innovation can offer pragmatic solutions to global environmental challenges.

Visit the Siemens blog to learn more about the CEE success story.

The post Proof is in the roast when an engineering company acquires a coffee maker appeared first on Engineering.com.

Most commercial drones still depend on a human pilot for mission planning, takeoff, landing and battery management. NxtQube asked a simple question two years ago: If drones are “unmanned,” why do they always need someone on the ground?

“Everyone is making drones, and we see a very large-scale adoption of drones, but they always need a pilot on ground to operate the mission,” explains NxtQube’s Director and CEO, Nikhil Rajput. The answer became the company’s mission, and today they build “drone ports,” which are self-sustaining docking stations that house, charge, control and automate off-the-shelf drones so they can operate 24/7 in remote or industrial environments without a pilot on site.

Rajput adds that the company is essentially building a drone infrastructure to fully automate field drone operations, which would empower drone manufacturers and DSPs (drone service providers) and, according to his predictions, help surpass even the most aggressive global predictions for the industry.

Scaling Drone Adoption

From border security and rescue operations to crop monitoring and infrastructure inspection, drones promise enormous value — but only if they can deploy reliably and at scale. Traditional workflows force pilots and equipment to be on-location, plan each mission manually, swap batteries and troubleshoot in the field. Those logistical hurdles keep many organizations from moving beyond proof-of-concept trials. NxtQube’s vision is to turn any site with power into an autonomous drone launchpad that pilots manage from a single web dashboard.

The company is introducing what they are calling a “Drone in a Box” (DiaB) that is a weatherproof, tamper-resistant robotic enclosure equipped with climate control, redundant electromechanical systems and five-hour backup power. The drone carries out all the tasks that a pilot would normally perform on field to ensure the flight on the designated route while being controlled remotely via our web dashboard. The system is compatible with standard drones and common drone manufacturers, meaning modularity for organizations planning to utilize it. Software built around open-source and proprietary protocols gives each dock decision-making autonomy, which allows it to monitor flight status, diagnose failures remotely and execute programmed missions without human intervention.

“In the first two and a half to three months of starting NxtQube, we were very clear that we have to be an agnostic platform, where drones from multiple manufacturers could operate. That’s why we built modularity into the company from day one,” says Rajput.

By decoupling drone flight from on-site pilots and supporting standard airframes from a variety of manufacturers, NxtQube makes autonomous drone fleets as easy to deploy as networked security cameras.

Digital Transformation Through Simulation

Simulation and digital twins have become a mainstay for large organizations that are looking to optimize efficiency. For their CAE, NxtQube is using hypermesh data in Solid Edge, as well as mechanical CAD features, to design and manufacture their docking stations.

“Simulation was always a key component of our development. We are also proud to mention that we are the Altair startup challenge winner in India in the category ‘Innovative Startup in Defense and Aerospace’. We did initially face a lot of issues of standardization. Eventually, we built an expertise in robotics and the simulations around it, making it more and more reliable,” Rajput explains.

Initial prototypes were functional, but over-built and heavy, which was driving up costs and shipment complexity. Through iterative cycles of design, simulation and refinement, the team shed over 60% of the dock’s weight while beefing up landing-gear robustness and electronics reliability. They began using FEA and beam analysis tools in Solid Edge Simulation for thermal, structural and fatigue analyses, to determine optimal material thicknesses and seal tolerances, extending the expected field drastically.

“I’m happy to say that we are easily estimating a life cycle of somewhere in the range of four and a half to five years. And I think that predominantly has happened because of simulation.”

Simulation also underpins docking-station manufacturing. Early runs revealed wear-and-tear on moving parts and electromagnetic interference in the electromechanical systems. Performing virtual fatigue testing and flow-dynamics modeling in Solid Edge helped the engineers redesign seals and cable routing, ensuring consistent IP-rated performance even after thousands of open-close cycles. Today, each unit endures weeks of automated downpour, dust-ingress and mechanical-cycle testing before it ships.

Solid Edge for Startups Fuels Rapid Innovation

Before deciding to use Solid Edge, Rajput was already familiar with Siemens NX. He credits some of NxtQube’s agile development to the Solid Edge software, accessed through the Solid Edge for Startups program. As a member, NxtQube leverages the full Solid Edge suite for mechanical CAD and CAE simulation without the budget pressures typical of high-end engineering tools.

“We evaluated a number of engineering software companies, but Solid Edge struck the perfect balance of power and simplicity. It handles our solid modeling, sheet-metal design, assembly management and large assemblies at a fraction of the cost of other enterprise packages,” says Rajput.

Solid Edge’s simulation tools provided feedback on stress concentrations and thermal hotspots, closing the loop between design and test. Version control and collaborative workflows ensure iterations go straight from engineering to manufacturing without costly mistakes or rework.

“We all came from basic CAD backgrounds, and Solid Edge helped us refine our designs, making our designing process more effective and much more optimized moving forward,” he adds. “Specifically, the simplicity and the resilience of software for part and assembly modeling will help us be quicker than our competitors.”

Meanwhile the team has also designed a drone port that houses the system in Solid Edge. It is weatherproof and tamper-resistant to ensure safety at remote locations. Additionally, it is equipped with a climate control station to ensure safe flights. The drone port is capable of battery swapping or battery charging for various applications. This is done either by contact or wireless charging.

Looking Ahead: Scaling Global Deployments

Rajput’s team has a background in manufacturing, but they weren’t experts in automation and robotics. To remedy this gap, the whole team took to refining their skills and developing a robust understanding of these areas. Initially, their manufacturing was limited in these areas and typically took the easiest, often more expensive routes. As they collected mentors and developed solid standard operating procedures (SOPs), Rajput’s team has been able to refine their design and manufacturing processes for better quality and scaling.

Now, with annual production capacity ramping from 150 to 300 drone ports this year, NxtQube is poised to meet demand from emergency services, agriculture, utilities and logistics providers worldwide.

“We have the capability of 150 docks at the moment, but getting to 300, 350 or even 500 would not be a challenge because all of the systems are based on these robust processes of scaling and building something to a global standard,” Rajput says. NxtQube already has strategic partnerships with drone manufacturers, system integrators and service-providers in India, with plans to expand.

As a next step, NxtQube also aims to build the world’s first Agentic AI Platform for drones — combining autonomous hardware (Diab Dock), intelligent mission software and drone data analytics (Virtual Pilot), and a command centre (Mission Dashboard) that enables pilotless, round-the-clock drone operations at scale.

To summarize, NxtQube continues to refine its autonomy platform by adding AI-driven decision-making at the dock, multi-drone swarm support and logistics-grade payload handling, Solid Edge for Startups will remain a cornerstone of its digital-transformation toolkit as they look to grow in the coming years. By marrying frugal hardware design with rigorous simulation, NxtQube is working to turn the dream of truly unmanned operations into a reality.

Visit Siemens to learn more about the Solid Edge for Startups program.

The post Automating Drone Field Operations: Making UAVs Truly Unmanned appeared first on Engineering.com.

Toolpath, the CAM startup using AI to automate toolpath creation, has a new investor, and who it is may surprise you (but it shouldn’t).

“Our new investor is Autodesk,” Al Whatmough, Toolpath CEO, told me. “This closes out all our seed funding.”

The companies didn’t disclose the amount of the investment, but Whatmough said it was part of the strategic investment round that closed in May 2025 and brought Toolpath’s funds to nearly $20 million. Toolmaker Kennametal led that round, which also included CAM kernel developer ModuleWorks.

“There was space in the round for a software leader,” Whatmough said. That Autodesk filled that space was only natural. For one thing, Whatmough was Autodesk’s director of product management for manufacturing until 2021. For another, Toolpath had an existing integration with Autodesk Fusion, which Whatmough praised as “the dominant cloud-based CAM system.”

“Nobody else is anywhere close,” he said. “Whether we had [Autodesk’s] investment or not, Fusion would still be the platform we put our automation on.”

With Autodesk’s investment, Toolpath can take the Fusion integration even further. Autodesk pointed out the potential in a blog post from Stephen Hooper, VP of cloud-based product design and manufacturing solutions.

“[Our investment] marks the start of a strategic partnership, enabling our two companies to integrate closed-loop, fully automated workflows into Autodesk Fusion. Looking ahead, combining Toolpath’s technology with Autodesk’s Manufacturing Data Model would enable Fusion users to automatically analyze manufacturability, plan machine strategies, and send complete programs to Fusion,” Hooper wrote.

When I last spoke with him, Whatmough told me that Toolpath planned to support other CAM systems beyond Fusion. I asked him if that’s still the case.

“Our focus is Fusion, just because there’s a core alignment in the current customers,” he said. “Fusion users, by definition, tend to be on the more innovative side. It’s the most modern CAM system. They don’t have a cloud aversion.”

That said, Whatmough emphasized that there’s nothing about Toolpath, either technically or obligatorily, that makes it exclusive to Fusion.

“When we think about CAM integration, it’s like a post processor for us,” he explained. “Today we output the instructions to grab onto the Fusion steering wheel. We’ll make an amazing experience there. Once we do that, we can open up to other CAM systems or directly to the machine.”

One more thing I learned from Whatmough: Toolpath is freely available for hobbyist use through this application process. If you try it out, let me know your thoughts at malba@wtwhmedia.com.

Jon on Onshape

This summer Onshape hit the memorable milestone of 200 updates. The cloud CAD platform is updated like clockwork every three weeks, so if you do the math you’ll find that time is moving a lot faster than it ought to for what I still think of as a fresh new CAD startup.

Thoughts of mortality aside, congratulations to Onshape.

To mark the occasion, I caught up with co-founder Jon Hirschtick to reflect on Onshape’s evolution and where it might go next. You can read all about it in Looking back on 200 releases of Onshape: Q&A with Jon Hirschtick.

Quick hits

• Coreform has released the latest version of its hex meshing software, Coreform Cubit 2025.8. The update introduces a “sleeker, more modern look” and provides “more robustness, better quality elements, and improved capabilities,” according to Coreform.
• Electromagnetic simulation software developer Nullspace announced $2.5 million in seed funding that it will use to “expand the engineering team, accelerate product development, and scale go-to-market efforts as we target growing demand across aerospace, defense, quantum computing, and AI-enabled hardware markets,” according to CEO Masha Petrova.
• CoLab, the Canadian company developing an AI-powered design review tool, commissioned a survey of engineering leaders and discovered, in a stroke of fortuitous validation, that “100% of survey respondents said that AI would speed up design review times.”

One last link

Don’t sit down to read this one: Design World contributor Mark Jones with Finding inspiration in unlikely places.

Got news, tips, comments, or complaints? Send them my way: malba@wtwhmedia.com.

The post Autodesk invests in AI CAM platform Toolpath appeared first on Engineering.com.

That Onshape would make it this far was no certainty back in 2012, when co-founder Jon Hirschtick assembled a team hoping to replicate the success of his prior venture—a little-known CAD program called Solidworks—but with a radical twist: the cloud. Hirschtick envisioned no more files, installations, or versions; Onshape would run in a browser, store your data online, and always be up to date.

Hirschtick’s cloud CAD gamble paid off. In 2019 PTC bought Onshape for $470 million, and over its 200 releases (202 at time of writing) Onshape has expanded from CAD to include simulation, rendering, computer-aided manufacturing, and an AI assistant, among other features.

But what’s coming next is even more exciting, Hirschtick told Engineering.com. We sat down with Onshape’s co-founder, now PTC’s chief evangelist, for his thoughts on how Onshape has evolved over the years and where he hopes it can go next.

The following transcript has been edited for brevity and clarity.

Engineering.com: What would the Jon Hirschtick of 2012 think of Onshape as it exists today? Is it what you expected it would become?

Jon Hirschtick: Not to say I saw the future exactly, but my first answer is yes, I think it is what I expected it to be. We set out to make a cloud-native professional CAD/PDM system. We set out to reach a lot of customers, from some of the largest companies to startups.

I would say that I didn’t see AI coming. We knew about machine learning and things, but we didn’t know about generative AI, and so I could not have known how powerful our advantages would be in the world of AI. It’s sort of a lucky win for us that a cloud-native platform is a big win for AI. I didn’t see that coming. I would not have imagined we’d have AI Advisor and all the things we’re planning on adding to it.

But everything else pretty much was part of the vision. And I’d say I feel lucky. A lot of times we have visions and we say, if that all happens, I’m going to feel awesome. And so I feel pretty awesome.

Thinking back over the 200 releases, are there any highlights that stand out for you as big moments in the history of Onshape?

Oh, there are plenty. There’s two dimensions of how we improve Onshape. One is what I call the depth of the product, meaning taking an area that we already have and adding more detailed functionality, adding more performance, maybe fixing some anomalies in how it works, cleaning up the user interface. I call that depth work.

And then we add breadth, where we add modules, areas of function we didn’t have before, like AI Advisor and CAM. I think it took us a number of years to have a decent breadth of product, to have drawings and sheet metal and weldments and now CAM and simulation and rendering.

I would say shipping CAM is a moment for me. Because not only did we make CAM available, cloud-native, fully embedded in Onshape, it also to me marks the last of what I’d call the significant breadth items. Now, I’m not saying we don’t have more to add. You always have more to add. But we’ve crossed a point where it’s kind of downhill sledding now on the breadth of the product. And so that’s one thing.

The other thing is AI Advisor. I think that was a watershed moment for us. Sure, everyone has demos. We have all kinds of AI prototypes and demos internally. Everyone’s doing that. But what I’m really proud of is that we shipped AI Advisor to all users. That’s a lot of people that have access to it, and it’s a value add tool, even at the pro level. You can take users that have been using Onshape for years, and they are getting help from AI Advisor.

200 releases from now, what do you hope Onshape will look like?

I think looking back 200 releases from now, I won’t be talking to you about adding breadth that we were missing relative to other products. I’ll be talking to you much more about adding breadth that takes us way beyond other systems. I think you’ll see that cloud-native and AI are the gifts that keep on giving.

The way you see real-time collaboration woven into the fabric of Onshape is a perfect and unique platform for bringing AI in. AI’s got to participate in the modeling as a real-time collaborator. In Onshape we’ll have an AI collaborator, I think, that will be in real time, present with you. This is not a guarantee, it’s not saying we’ll release it. I think we’ll see AI helping engineers as a valued companion. Think Jarvis in Iron Man. I think we’re going to see that. I hope we see that.

I also think we’re going to see more and more amounts of massive data and compute put to work for the benefit of the user through the power of a cloud-native system. And I think that our three week release cycle is going to become not just a catch up cadence of features, it’s going to become the cadence of innovation and improvement. It’s always been a mix of innovation and adding features everyone knew we needed, and I think that balance is shifting. The next 200 releases will be much more about agile innovation and things where you’ll go, wow, never heard of that.

At the end of the day, it’s not about what we ship. The real way I’ll measure 200 releases from now is: How much are we able to help people produce better products? And I think we can do a lot more. I think we’re only half done as an industry with what we can do for people and how large an impact we’re making, and I believe both of those can grow enormously in the next 200 releases.

AI Advisor came out in beta a few months ago. How has that gone and what have you learned so far?

It’s gone really great. I’m happy with what it’s done already, but I’m excited about what we can expand it to do in the future.

We tried to ship something that would be useful to pro users, and we’ve achieved that. You can see that in our forums. Just shipping AI at the scale we operate at Onshape, and doing it in a way that’s secure and performant and reliable, is a big thing to do in our world. To do that is a pretty big lift, and big thanks to our friends at AWS for all the tools they give us. Anyone can go to AWS and use the tools, but we’ve announced a strategic partnership with them, which means that we’re working extra closely with AWS on this.

I’d like it to do more. It has a modest range of capability right now. I was just looking at videos of some of the prototypes we have for expanding what AI Advisor does. We’re looking at a lot of great things.

I asked for some feedback from the team on surprising things we learned. One is it’s used in an even more conversational way than was originally imagined, which is great. We want conversation. We kind of worried people would use it more like a traditional Help tool, like, I want to build a G2 surface, where’s the documentation for that? Actually, people are having longer conversations, which we think is very promising, because the more context you give to an AI tool, the better the answer.

People tend to use non-Onshape terminology more than we expected. I guess they feel like they’re talking to a person more, and they don’t have to be as tight on their terminology. So instead of saying, how do I do a modal simulation, they might say, does Onshape do natural frequency analysis? Which is sort of the same thing, but different words. So we have to think about that.

There are a lot of requests to do work with the API and FeatureScript, which we sort of knew was coming, but it’s higher than we thought. People know about FeatureScript, but it’s a certain bar to learn to program it.

People like to say thank you to the AI. And repeat usage is higher than expected, meaning that people come back more than once. The share of one-and-done users is lower than we had forecast, which is a good thing. So these are all good, but again, it’s rev one in a journey.

What can you say about the other AI features you’re working on?

We’re very excited about AI for rendering. I don’t want to say exactly what will ship or not, but we see a number of AI use cases in rendering that are very exciting.

I’d like to think that you’ll see AI Advisor start to get more proactive with creating and editing your models and assisting you using our API, using FeatureScript. That’s not a commitment that we’re going to release it, but those would be things that excite me.

I’d like to see AI giving you very specific advice to your model. Now if you say, how do I make a better quality surface? It will give you details on that. But if you say, I want to make this surface that I’m pointing at better quality, right now our AI Advisor doesn’t do that. And we hope to do it.

The post Looking back on 200 releases of Onshape: Q&A with Jon Hirschtick appeared first on Engineering.com.

Ansys, now a part of Synopsys, has signed an agreement with Nvidia to license, sell, and support Nvidia’s Omniverse technology embedded in Ansys’s simulation software.

According to Ansys, the deal will allow it to deliver easy access to Omniverse technologies and libraries, starting with CFD and autonomous solutions.

“Visualizing fluid dynamics in physically based digital environments enables engineers to analyze complex datasets more intuitively, resulting in smarter, faster design optimization for even the most challenging engineering tasks,” reads Ansys’ announcement.

Nvidia’s Omniverse is expanding lately. Just a couple weeks ago Nvidia and PTC announced a similar integration for Creo and Windchill, and not long before that Nvidia and Tech Soft 3D teamed up to bolster OpenUSD, the 3D file framework used in Omniverse. Both PTC and Tech Soft 3D also joined the Alliance for OpenUSD (AOUSD), which Nvidia co-founded two years ago. Ansys already joined the AOUSD in yet another collaboration with Nvidia in March 2024.

In other Omniverse news, Nvidia announced new Omniverse libraries and SDKs for robotics development and deployment. You can read more about those here.

Vectorworks 2026 coming this September

Vectorworks has announced details of its upcoming software release, Vectorworks 2026. The design and BIM platform will be available this September with new features that Vectorworks says will optimize several major workflows.

One is that Vectorworks Cloud Services will be integrated directly into the Vectorworks 2026 desktop application, allowing users to leverage cloud computing resources without leaving the program. Vectorworks 2026 also includes a new tool called the File Health Checker palette that “helps keep files in optimal condition and ensures that projects run smoothly and efficiently, especially when integrating files from external sources.” In particular, the cloud will process large Revit file imports in the background.

Another new feature of Vectorworks 2026 is the Sustainability Dashboard, a hub providing real-time insight into compliance targets including embodied carbon calculations, biodiversity net gain, and other metrics.

For more details on Vectorworks 2026, see Vectorworks.com.

Engys releases Helyx 4.4.0

Engys has released Helyx 4.4.0, the latest version of its general purpose CFD software, as well as updated versions of its add-ons Helyx-Coupled, Helyx-Adjoint, and Helyx-Marine.

Helyx 4.4.0 adds several features including a remote file browser, which allows users to browse directly from the Helyx interface via SSH; enhanced geometry tools, including the ability to import Rhino 3DM files; new meshing capabilities, including new options for isotropic, anisotropic, and cylindrical base meshes; new setup features, including new porous media thermal models; and new post-processing tools, including improved runtime visualization. The latest release also includes solver and performance enhancements, according to Engys.

Kubotek Kosmos releases MBD File Utilities 7.1

Kubotek Kosmos, developer of the direct CAD modeler KeyCreator, has released version 7.1 of its MBD File Utilities software suite.

The update extends CAD file support to Dassault Systèmes Catia V5 2025, Autodesk Fusion and Inventor 2026 formats, and Siemens NX 2412 and Parasolid 37.1. View and Convert, two of the four MBD File Utilities, also add support for reading STEP XML 3D assembly structures.

The new version also includes quality of life improvements across the MBD File Utilities suite, such as enhancements to saved views and text attributes that always face the display plane.

One last link

If you’ve ever seen, inhabited, or built a building, don’t miss Marc Ambasna-Jones’ latest article for Engineering.com: How software is redefining sustainable building engineering.

Got news, tips, comments, or complaints? Send them my way: malba@wtwhmedia.com.

The post Ansys and Nvidia strike deal for easier Omniverse access in simulation appeared first on Engineering.com.

Of course, the hardware alone doesn’t get you very far. Software with support for spatial computing is growing by the day. Some CAD programs support VR directly, allowing designers to easily switch to a virtual view of their models. Other software caters to VR design reviews with features for collaboration and markup. Game engine software, sometimes called real-time 3D software, can be used to develop custom AR or VR experiences using existing CAD models.

Though there’s an upfront cost to getting started with spatial computing—both in the price of headsets and software as well as the learning curve for users—for many engineers, the cost is well worth it. VR provides an unparalleled way to visualize and refine a design, and has thus become a part of many engineering workflows.

In this article, we’ll look more closely at the main ways engineers, architects, manufacturers and others are using spatial computing.

Visualization and collaboration

By strapping on a mixed reality (MR) headset or peering through an AR-capable phone or tablet, engineers can see their work as if it were in the real world. This isn’t a gimmick—engineers, after all, design products for the real world, and so visualizing it in place rather than on a computer monitor is an obvious advantage.

Besides the depth and perspective that spatial computing provides to visualization, another important benefit is scale. An engineer designing a small bracket could see that product in life size using a screen, but anything bigger than a computer monitor would be an exercise in imagination (even the most multi of monitor setups can’t fit a car, airplane or space station). With spatial computing, all designers have the opportunity to visualize their designs at scale.

This spatial computing benefit is most readily apparent to designers of, unsurprisingly, spaces. Architects, for instance, can use VR to virtually walk through their building designs, achieving a sense of the space that’s simply impossible through traditional computing. This walkthrough need not be limited to a static showcase, either. Inside VR, designers have the opportunity to make changes on a whim. Don’t like that material finish, that lighting, that façade? A few clicks of your VR controller and you can see it in any number of options. Want to change the time of day, the season of the year, the weather? Go for it. You’re in a virtual world; you control every aspect of it.

Regardless of what you’re designing, spatial computing gives you the ability to visualize it more realistically than ever. But you don’t have to be alone in your virtual world. Another big advantage of spatial computing is that it provides a three-dimensional meeting space. Putting the two together, VR gives engineering teams a way to conduct virtual design reviews with participants from around the globe. In these virtual meeting rooms, participants—who are often represented by virtual avatars—can walk around, talk about, and review 3D models as if they were evaluating a real prototype. Not only does this save the costs of manufacturing and travel, it allows engineering teams to iterate faster and develop better end products.

Factory planning, maintenance and optimization

There are many ways that engineers can use spatial computing for manufacturing. In the same way that an architect can walk through a virtual building, a factory planner can use VR to see a virtual layout of their facility. This realistic and immersive visualization allows them to not just see but experience problems, such as machinery collisions or insufficient spacing, that might otherwise go undetected.

Spatial computing also provides the opportunity to simulate how factory workers interact with the environment, a crucial step for optimizing ergonomics. Even if a process seems fine on a computer monitor, stepping into a VR version of it would make it readily apparent that workers would have to, say, bend down too much to grab the next component. It’s a fix that’s all the simpler for catching it in advance.

AR and VR can both improve the process of equipment maintenance as well. This might take the form of an augmented video call between a worker and an off-site maintenance technician, who could annotate a piece of equipment from afar while the worker sees the notes, in place on the equipment, through an AR-enabled tablet. The technician might have learned about the equipment from a VR manual, virtually taking it apart and putting it back together.

Another popular use case for VR is for operator training, as it provides an unparalleled platform to simulate different scenarios. This could be used to train workers on their core job and beyond. For example, a VR simulation of a factory fire or hazardous spill could get every employee viscerally comfortable with emergency procedures.

Presentations and marketing

The immersive experience of spatial computing is a natural fit for showing off your product, whether internally or externally. For the same reasons that engineers and architects enjoy VR for design visualization and collaboration, the technology is a great option for presenting product concepts to others within an organization. Sketches and renders are nice, but they don’t beat life-like representation in a real environment.

Similarly, consumers increasingly appreciate—in some categories, even expect—spatial computing models that they can try on at home, so to speak. This is particularly common for products with lots of aesthetic variation, such as furniture. It may be difficult to pick out the perfect sectional in a brightly-lit showroom, but if you were able to compare options in your own home, the choice would be much easier. All you need is an AR-capable phone—and for the manufacturer to give you an AR option on their website. Combined with configuration tools, spatial computing gives potential customers the most convincing and personalized sales pitch you could imagine.

The post How are engineers using spatial computing? appeared first on Engineering.com.