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Visual Collaboration and Communication in Design and Manufacturing Using VRED

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Description

In this industry talk on visual collaboration and communication in design and manufacturing using VRED software, you will gain valuable insights that can enhance your product development process. The course will explore the importance of visual collaboration and communication, capitalizing on innovative technologies such as virtual reality (VR), augmented reality (AR), and high-end rendering. You will learn how VRED integrates with these technologies to facilitate digital prototyping, remote collaboration, and streaming of design data. Additionally, the course will emphasize the advantages of cloud-based solutions for seamless access to project data and the use of high-end rendering capabilities. Real-world use-case examples will demonstrate the transformative impact these technologies have on communication, commitment, and sales.

Key Learnings

  • Learn about the significance of visual collaboration and communication in the product development process.
  • Explore the technical features of VRED that facilitate collaboration and digital prototyping.
  • Discover the application of this technology to enhance design and manufacturing processes.
  • Learn how a single data set can effectively support various workflows, enabling visual collaboration and communication.

Speakers

  • Avatar for Pascal Seifert
    Pascal Seifert
    Pascal Seifert studied design at the Anhalt University of Applied Sciences from 2002 to 2007. He has been working in the automotive-design visualization and virtual-reality domain since 2008, and he has developed a variety of qualities and skills in the whole virtual-product lifecycle process. He possesses expert knowledge in database, handling file conversion and data preparation, and he presents the results in design or immersive engineering environments. Currently, he is the Technical Product Manager for Autodesk VRED and caretaker for automotive customers around the globe, using his design and visualization experience to help during the digital design phase.
  • Lukas Fäth
    Lukas Fäth joined Autodesk, in 2012 with the acquisition of PI-VR. After graduating in digital media Lukas drove in the visual and conceptual development of the VRED high-end virtual prototyping software. He was responsible for quality assurance, support, and consulting, and is a professional VRED software trainer for the automotive industry and computer-generated imagery agencies with a strong artistic knowledge base. He is now taking care of product management for the Automotive Visualization and XR.
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Transcript

LUKAS FAETH: Welcome, everybody, to our presentation today about visual collaboration and communication design and manufacturing using Autodesk VRED. My name is Lukas, and I'm joined by my colleague Pascal. We are both from the automotive product management team, and we are happy to present this topic to you today as part of the AU 2023.

So before we start, let's take a look at the industry context. Visual collaboration and communication in the context of industries beyond automotive. We called it in manufacturing and design, but actually, we are going to look at also AC topics, so basically everything that is beyond Autodesk VRED's typical application area, which is the industry of automotive design and engineering.

So why are we doing that? Because the challenges that our customer facing are pretty similar in all those industries. So on the one hand, you do have things like daily iterations, and product development, and projects that are not easily accessible for everybody. So not all the stakeholders have access to the digital prototype all the time.

This is the same in automotive. This is the same in D&M, but also in AEC and beyond. So other challenges that our customers are facing or sharing between industries is inefficient communication. And a lot of that is related to inefficient communication tools or the lack of a good digital prototype, which could be used as the base for communication. That's also something that we are addressing with this VCC, which is the abbreviation for visual collaboration and communication solution that we're talking about today.

A very important pillar for a reliable physical prototype or for a reliable digital prototype is the visual quality of it because if you look at it, you want to take decisions just as on a physical prototype. So it needs to be realistic. It needs to be in the same complexity than the physical prototype would be and needs to be represented accurately so you can take those decisions. This is a challenge in itself, which VCC is addressing.

Then, of course, you want to integrate your end customers. And this could be an individual, like in consumer products, but this could also be a huge company, like if you're creating, I don't know, industrial machinery, or if you're building factories for automotive OEM. In all those cases, you want to involve them early in the design and engineering process to get their input as well.

So this element plays into the challenges as well. Stakeholders that are internally need to be connected as well. So the workforce that is working on the project needs to work around this one digital prototype and have one source of communication. And then on top of that, of course, the aggregation of very complex data.

These are the challenges that we are looking into today and see how VCC is solving them for every industry, yeah, or a mix of industries beyond automotive. So I talked about VCC. We all know this is the abbreviation for the topic we talk about today.

Let's take a look at what it actually is. And you can see that we are starting from the bottom to the top. So in the bottom, there's the product development layer. Let's say this is Inventor because we have an industrial or a machine here.

There's an aggregation of data. There's a creation of data. And this data set is built. This data flows into the middle layer, which is VRED building this one single data set that can be used for different disciplines. And we'll look at that in a second.

And of course, this is giving us the accessibility to everybody around the whole world. So all the collaboration features of VCC and of VRED are helping to bring in all the stakeholders we talked about and the challenges one slide before. So we're basically taking a very complex data set from experts and specialized individuals into one data layer that everybody can access and collaborate on.

And all of that is around the digital experience. So it's all about access. It's about making it easy. And it's about making it realistic to interact with the digital prototype. You can see-- and I brought some automotive examples in the videos here on the right side, where we see the VRED XR capabilities, but also engineering use cases where ergonomic studies or reachability studies-- so it's not just about seeing it.

It's not-- it's always depending on the digital prototype if you want-- how we want to experience it. Sometimes it's about the visual fidelity. Sometimes it's about, in this case, airflow, or it's about reachability if you can reach something, if you can navigate in a certain HMI.

There's the communicational aspect in that as well, as you can see here. So draw over physical prototypes. There's a collaborative aspect, as you can see in this, where Inventor and VRED are connected in real time. And somebody's changing things in Inventor. Somebody views it on a tablet, another one on a XD device or an XR device.

So there's a huge variety about what digital experience in this context means. And that's why the output performance needs to be as flexible as possible as well. And this is where VRED or VCC, in combination with VRED, is perfectly suitable, as you can see here, with a huge variety of very easy-to-use output formats that can be used on any device, even streamed through a tablet.

So it doesn't matter if you have the expertise to deal with the digital prototype. It doesn't matter if you have the hardware. Everybody can access it, and work with it, and communicate around it.

Why is that important now? It is always important, or it was always important. And in the automotive industry, this has been ongoing for several years already. But now, we see a huge push for gaining more efficiencies and realizing efficiencies at our customers to remain competitive.

So when we talk to customers about what's their biggest pressure, what's the biggest goal they want to achieve, we go away from, or they go away from saying feature x, y, z, and they go into saying we need to collaborate better. We need to communicate better.

So those high-level themes are repetitive for our customers to stay competitive in their individual area, may be auto, may be consumer products, so on and so forth. Also, COVID-19 impacted the way, how we work. A lot of people are now working from home. Teams are more dispersed around the globe.

And it's a new normal that people are not sitting in the same office. And this also comes with the problem of not having access to physical prototypes, right? You cannot send them around.

So it's all about sharing them easily, giving people access to that one digital representation of the product that you're building from anywhere, on any device, and being able to provide their input. And of course-- we touched that lightly in the challenges already-- it is important to involve the end customer in the early design and engineering phase to get their feedback quickly and realize or build the products they love quicker and faster.

So summarizing those industry outcomes-- and as I said, this is across industry in three different buckets. We have the possibility to collaboratively experience and validate the prototype at any stage of the process. Then we're the possibility to take decisions with confidence and, at the same time, have more iterations, which consequentially allows you to build better products, and of course, to communicate easily.

And this is meant internally, with the stakeholders, and have the collaboration around it, but also later on in the process externally if you want to promote or market your product. And we talked a lot about different aspects of it. I brought a video, which is summarizing the capabilities of Autodesk VRED pretty easily and puts it to one point. So let's just listen to that video for a second.

[VIDEO PLAYBACK]

- You build amazing things that move the world forward. But before it's amazing, it's a prototype-- many prototypes that let you see every last detail so you can make every last decision on your design journey with precision.

While physical prototypes are necessary, they are expensive, time-consuming, and limiting, slowing down your product development processes and your time-to-market. And with VRED from Autodesk, photorealistic digital models are easy. VRED allows anyone to create digital prototypes so accurate and reliable that you can actually make informed design and engineering decisions, add many steps in the development process.

VRED quickly transforms huge amounts of complex design and engineering data into compelling, high-fidelity images, animations, and real-time presentations-- visualizations that you can then share in any format, to any device, with anyone, allowing everyone that's a part of your process, from designers and engineers to marketers and executives, to easily review, showcase, and evaluate digital prototypes from anywhere.

So whether you're a small team with a simple process or a large enterprise with a highly complex product development process across many departments, your teams can collaborate better, make decisions faster, and drive amazing products to market sooner.

Discover how VRED can accelerate your business. Contact us today.

[END PLAYBACK]

That's a great summary of what Autodesk VRED is. Let's quickly take a look at where it comes from. And as we said already, it's coming from the automotive industry. So it is the predominant visualization and digital prototyping tool in the automotive industry. Basically, it's used to assemble a full, configurable data set of a car, realistic representation of it.

So you can play around with different trim lines, with different material combinations. But at the end, it is also-- or it's representing the full car as it is brought to market in different regions with the logic behind it, where a certain line or a certain version of a car can be bought.

As you can see here, there's inbuilt, collaborative functionality in virtual reality, but also in different other output formats. Basically, it doesn't matter what device you're on. You can collaborate, and as you can see here also, with a lot of people.

So we have customers that collaborate in XR with up to 40, 4-0, individuals at the same time, around one data set. And VRED has a very specific value proposition, which is consisting out of three different values that make it a great tool for visual communication, digital prototyping, and decision-making.

One is the maximum efficient enterprise visualization data pipeline, meaning we can accumulate huge data sets and build and review data sets with billions of polygons and huge amounts of data. And Pascal is going to show you some of those examples later on in his part of the presentation.

The second very important element for VRED's value proposition is the accurate rendering, the high performance and rendering, and the scalability of the rendering. So the visualization can be anything from very low end, high FPS gaming-like visualization to-- up to simulation-grade light visualization.

Again, we'll see some examples later on. And the third pillar that concludes the value proposition for VRED is collaboration from anywhere at any time. This is the collaboration, collaborative aspect that we saw in the videos already, combined with streaming capabilities that you can leverage. So basically, VRED can be used from the cloud and streamed to any device in collaboration with desktop or other devices.

And the accumulation of that data, how could that look like? So let's have a quick look on how you could assemble this flexible digital twin. So first of all, VRED is able to consume a huge amount of different data types. This could be ordered as tools, but also a huge variety of cut CAD files.

We can bring them in. We can even keep the NURBS data in the background and reference the data in. So it's easy for you to update it, and you can accumulate ths prototype. So basically, you could import a machine or something.

You could even enrich the data set with a great environment. Take some material libraries and download some libraries. Apply them to it. And then if something changes, you can just easily update it on the fly in the original creation tool, and VRED will automatically realize that and update the file itself.

So it's easy to maintain those digital twins, also, in collaboration or digital prototypes. And then, as we said already, there's different varieties of output devices and formats. On the one hand, we have mobile devices like cell phones or tablets, but also ultrabooks, which are not capable to run the product itself but need a streamed result-- same quality as if it would run on the machine.

Second is desktop and power walls. So desktop, just a regular, very capable machine to use the visualization tool natively on the machine, and power wall, representing a bigger review facility, like a huge projection or a huge LED display.

Then we have XR. And in this example, you can see a tablet XR application. But of course, we are also supporting a huge variety of head-mounted displays, XR and virtual reality displays. And then you can also use it to generate assets that you want to use somewhere else. So this digital prototype can be used downstream in other applications and be exported.

And of course, you can create images and animations, so basically offline assets like this catalog that you can use for print or for online usage. And all of this can be done in collaboration. So there is no, like, separation between the different use cases of the product.

All of this can be done mixed up and be done in collaboration. And how would that VCC solution look like in the cycle that we're creating? So basically, as we said, there's the creation. Then there is the VCC element itself with Autodesk VRED, which allows us all the capabilities we talked about.

And you are working around this digital prototype. And then there's the communication phase, where you either identify an error, or you get a sign-off, like a positive outcome, or you get input from a stakeholder, or you talk about a design change or an engineering change that you want to apply.

And this feedback can be fed back into the creation process again. Changes will be done. We talked about that. VRED scene will automatically update through referencing. And then the cycle goes on and on until the final product is done. This is speeding up things dramatically and making the life of everybody involved in the design and engineering process way, way easier.

Quick look to the product portfolio until-- and afterwards, I'll hand over to Pascal, giving you some more detailed examples of how it can be applied in different industries. So we have different products. We have VRED Presenter, VRED Designer, and VRED Professional, which are running natively on, like, machines, like on Windows machines, on Linux machines, on desktops.

Then we do have two cloud products as well. So as you can see, the first three can run on devices, of course not on a tablet because it is too-- it doesn't have the computation power required. But in those cases, like tablet or ultrabooks, or cell phones, we can stream from the cloud with VRED Core or VRED Render Node. And yeah, stream either through shotgrid, which we have a great integration into, or directly through your native web page or web application, and bring it through the web browser onto your mobile device of choice.

So with that being said, we are going to look at a vast variety of different industries and how we could apply the product and the VCC solution to today. Pascal is going to give us some insights. You'll see a sneak peek here already of different elements. And as we already talked about, it has different criteria, different things that are important to it, like design review and training for industrial machinery and building factories and plants.

But also, sometimes the environment is more important, like the actual space you're building something in, like in retail or in factory, but also aesthetics, or emotions, or configurations could be important for consumer products. So very vast set of requirements and focus areas for the different industries.

All of them are covered with VCC and Autodesk VRED. And with that being said, I'll hand it over to my colleague Pascal, who's giving-- as I said, giving you some examples and more precise examples how it could be applied in the different industries. So with that being said, Pascal, please take it away.

PASCAL SEIFERT: Thanks, Lukas. I take it from here. And our initial example illustrates the role of real-time visualization in end-to-end retail store planning and layout. By importing data from Revit, SketchUp, or other content libraries into VRED, the process of experimenting with basic elements and configurations can commence earlier, enabling efficient use of available space.

Brands employ diverse strategies to navigate customers through their stores. Some prioritize a highly organized layout for better product discovery, while others intentionally guide customers through their stores to encourage unplanned purchases. VRED, as a real-time rendering application, allows to experiment with different product placements, quantities, and sequences in the customer journey, as this is a critical aspect for store planning.

VRED XR capabilities is a perfect vehicle to try out those scenarios virtually with test customers from all around the world without building test stores physically, on site. Moreover, brands try to aim to provide their loyal customers with novel store experience regularly using variation of colors, mirrors, deco elements, and lighting concepts to maintain appeal.

And again, those two sets in VRED-- in particular, the variant sets-- allow an easy setup of configuration and logic to experiment with. Lighting, in particular, is a noteworthy factor in store planning because retail stores are often located in large malls with limited natural light so they require substantial artificial lighting.

Furthermore, different light recipes or color temperature can be utilized to attract customers to a specific product and enhance their visual appearance. And in the next example, I'd like to talk about the importance of light a bit more.

In this example, we have a client who operates in the lighting industry, but on a much larger scale, such as in a wholesale market hall. This client is specialized in creating large-scale lighting concepts involving hundreds of thousands of ceiling light panels and individual spotlights for product illumination. They apply specific lighting recipes to items like groceries, which require different lighting temperatures to appear fresh and appealing.

Their goal is to create a uniform lighting concept while also providing individual product lighting. Autodesk VRED offers them two critical features for simulation tasks involving direct and indirect illumination. Firstly, a highly efficient and precise real-time ray tracer that can manage large data sets. Real-time ray tracing enables them to modify light intensity, temperatures, and materials, and instantly observe the visual impact. Secondly, Autodesk VRED provides several analytic modes that allow for better differentiation of intensity values with a false color rendering, like you can see here in the image. This is particularly useful when the onscreen image reaches a certain brightness level of appearance [INAUDIBLE].

A third feature of VRED that proves beneficial, not just for this specific client, it's the ability to handle metadata or BIM data, which is extensively used in the AEC sector. VRED supports the import of more than over 40 different CAD formats, including IFC. And IFC is the main data exchange format in the AEC and vector industry, not only containing geometry, but also a lot of BIM or metadata.

And having access to these BIM or metadata information in VRED is great, especially for large data sets, as it's nearly impossible to comprehend the content and structure of such an extensive scene in a short time for a visualization user. In the given example, the user is seeking for furniture from a specific supplier in the scene.

The initial metadata search returns all tables, chairs, and shelves, prompting the user to search further in the metadata to pinpoint what they are looking for to then perform a certain visualization task, like applying materials or replace the furniture with high-quality models. Last year, we talked about a project combining AEC consumer products and consumer-- AEC and consumer products that demonstrates how VRED is acting as a platform.

This example shows how VRED can be utilized as a valuable tool for visual collaboration, communication, and also digital prototyping. We have used a range of technology, such as XR, advanced lighting computation, and streaming to involve the customer from the outset. This collaborative decision-making process kept everyone informed throughout the design and planning process, ensuring the result aligns with the customer expectation and making the customer journey more inclusive.

Here, you can see the example where we streamed the content from VRED on a desktop machine onto a tablet, allowing the user to navigate through the scene and explore it on their own. And even bringing content to YouTube is possible if that's a cheap alternative to share content with clients. We imported and prepared data from Revit, Inventor, and Fusion 360, and VRED for a diverse set of review and evaluation purposes.

Autodesk VRED acts as a visual platform to aggregate all elements needed to take decisions and present design proposals to the customer. If you're interested to learn more, please visit our last year AU presentation on the Autodesk University website and look for visualizing digital prototypes in context with Autodesk VRED.

Let's switch gears a little bit from AEC, and let us show how VRED is used in factory design and planning. This video demonstrates an integrated factory model that brings together various disciplines, including infrastructure, building MEP, factory and product design. It showcases the use of VRED to visualize information that is stored centralized by streaming it on a tablet.

This allows viewers to explore a scale model or the entire factory in real-life size, incorporating supplier data to make informed decisions at an early stage. Streaming VRED content from either a desktop PC or the cloud enables the ability to stream to any mobile device, overcoming hardware limitations and ensuring compatibility across different operating systems. In addition, collaborative virtual reality sessions and factory planning enable individual-- enables individuals from different locations to convince, engage in discussions, and experiment the product or entire product line in a one-to-one scale.

These first-person VR reviews are particularly valuable for evaluating ergonomics or security aspects, as certain scenarios may be challenging to assess on a screen but become apparent when viewed in real-world size from the first-person view. Let's proceed to explore how VRED can be utilized in the industrial machinery sector for assembling large data sets. These data sets can be reviewed, validated, tested, and experienced with high visual fidelity, like the examples before. A very valuable use case is training machine operators in XR so they can experience their future workplace prior to sitting in the real-world one.

What you are seeing in this video is an Inventor model, combining about 6,000 individual parts, assembled into a main assembly of 30,000 parts. An additional 50,000 instances of rocks and bushes are included just for the environment, totaling to 1 billion triangles. VRED natively supports Inventor assemblies and parts, maintaining the original structure, references, and metadata, which simplifies the process of updating parts in your visualization scene, while the Inventor model is still under development.

DG Design, a design agency based in the UK, utilizes VRED during the initial design phase to generate visual assets for effective communication with their client. They employ VRED for digital design reviews, enabling them to inform their clients about various design decisions throughout the process.

Additionally, they leverage VRED's XR capabilities to conduct reachability and visual ergonomics from the operator's perspective. Particularly in the early stage of the form follows function design phase, where packaging and ergonomics significantly impact design iterations, VRED proves to be highly valuable for them, saving both time and effort.

We talked about AC and factories as well as heavy machinery in the last slides. And of course, those aspects can be used for the oil and gas industry or mining industry as well. Again, VRED is capable to load the full data sets and allow similar evaluation methods, as discussed before, but in a different industry.

A different industry is a good point. So now let's have a look at consumer and luxury products that have distinct visual requirements for visualization tool in contrast to the examples we previously shown, where data size and complexity matters more. In the case of luxury goods-- apparel or footwear-- the visual aesthetics hold a greater significance, often relying on minute details to achieve realism.

And as you can see in the video, the focus is mainly on materials, lighting, and surface structure as well as all the little details of this luxury watch. Consumer products usually require high quality or measured materials, incorporating physical effects, like dispersion, caustics, or subsurface scattering.

And moreover, there is an emphasis on artistic freedom when it comes to product lighting and camera setups, aiming to showcase the product in the best possible light, of course. This diamond, you can see here, is a perfect example for showing the effect of dispersion in translucent materials, where the white light is separated into its color spectrum, showing all colors of the rainbow inside the object.

And those results can only be simulated with highly physical, accurate rendering techniques, such as spectral rendering that VRED offers. The apparel and footwear industry in particular places a significant emphasis on the use of high-quality, measured, and also artistic materials. To meet the demands, VRED offers support for a wide range of industry standard materials, including [INAUDIBLE] materials, substance, MDL, and material X.

Additionally, those products often feature a wide range of variations in terms of materials and colors, which need to be efficiently managed or rendered automatically. And the variant set manager in VRED and automatic rendering capabilities are a perfect fit for this industry. The materials used in this example come from libraries and measured from physical examples using the [INAUDIBLE] Tech 7. And with that, I'd like to hand over to my colleague Lukas back for the last slide.

LUKAS FAETH: Yeah, so let's go back to the beginning, not just of the presentation, but also from the original VRED, right? We talked about that in the beginning. It's coming from the automotive industry. But as Pascal just showed in the last examples, it can be, and it is, applied beyond automotive a lot as well.

So in this case, you can see Rivian showing how they use VRED, how they leverage it for XR in the design phase for color material and-- color material decisions, let's say, to evaluate what material combinations should be applied in the car to check variations on the wheels and on other aspects. But also, as you can very impressively see, on how to put that product to market, how they market it, present it to customers, and advertise it, but also how they sell it.

Selling digitally is a big thing as well, which gets bigger and bigger. And that's why this digital prototype makes more and more sense and will be used throughout the whole process. So in automotive, we are already talking about covering the whole pipeline of the design, life cycle, the product design life cycle from design through engineering, through manufacturing, to sales.

OK, so with that being said, I think we are at the end of our presentation. So I hope we could tell you something about VRED that you didn't know in advance, how it can be used beyond the automotive industry because often, there's the impression that it is an automotive-specific tool. Think the examples we showed are demonstrating that it is not the case, that yes, it is solving issues for the automotive industry.

But also, the same issues and challenges apply to other industries. And that's a great reason VRED and also the VCC solution can be used beyond automotive. Yeah, with that being said, let's advance to the last slide. And thank you very much, everybody, for listening. As I said, I hope you learned something, and see you next year.

______
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We use Upsellit to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Upsellit Privacy Policy
CJ Affiliates
We use CJ Affiliates to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. CJ Affiliates Privacy Policy
Commission Factory
We use Commission Factory to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Commission Factory Privacy Policy
Google Analytics (Strictly Necessary)
We use Google Analytics (Strictly Necessary) to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Google Analytics (Strictly Necessary) Privacy Policy
Typepad Stats
We use Typepad Stats to collect data about your behaviour on our sites. This may include pages you’ve visited. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our platform to provide the most relevant content. This allows us to enhance your overall user experience. Typepad Stats Privacy Policy
Geo Targetly
We use Geo Targetly to direct website visitors to the most appropriate web page and/or serve tailored content based on their location. Geo Targetly uses the IP address of a website visitor to determine the approximate location of the visitor’s device. This helps ensure that the visitor views content in their (most likely) local language.Geo Targetly Privacy Policy
SpeedCurve
We use SpeedCurve to monitor and measure the performance of your website experience by measuring web page load times as well as the responsiveness of subsequent elements such as images, scripts, and text.SpeedCurve Privacy Policy
Qualified
Qualified is the Autodesk Live Chat agent platform. This platform provides services to allow our customers to communicate in real-time with Autodesk support. We may collect unique ID for specific browser sessions during a chat. Qualified Privacy Policy

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Improve your experience – allows us to show you what is relevant to you

Google Optimize
We use Google Optimize to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Google Optimize Privacy Policy
ClickTale
We use ClickTale to better understand where you may encounter difficulties with our sites. We use session recording to help us see how you interact with our sites, including any elements on our pages. Your Personally Identifiable Information is masked and is not collected. ClickTale Privacy Policy
OneSignal
We use OneSignal to deploy digital advertising on sites supported by OneSignal. Ads are based on both OneSignal data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that OneSignal has collected from you. We use the data that we provide to OneSignal to better customize your digital advertising experience and present you with more relevant ads. OneSignal Privacy Policy
Optimizely
We use Optimizely to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Optimizely Privacy Policy
Amplitude
We use Amplitude to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Amplitude Privacy Policy
Snowplow
We use Snowplow to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Snowplow Privacy Policy
UserVoice
We use UserVoice to collect data about your behaviour on our sites. This may include pages you’ve visited. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our platform to provide the most relevant content. This allows us to enhance your overall user experience. UserVoice Privacy Policy
Clearbit
Clearbit allows real-time data enrichment to provide a personalized and relevant experience to our customers. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID.Clearbit Privacy Policy
YouTube
YouTube is a video sharing platform which allows users to view and share embedded videos on our websites. YouTube provides viewership metrics on video performance. YouTube Privacy Policy

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Customize your advertising – permits us to offer targeted advertising to you

Adobe Analytics
We use Adobe Analytics to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Adobe Analytics Privacy Policy
Google Analytics (Web Analytics)
We use Google Analytics (Web Analytics) to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Google Analytics (Web Analytics) Privacy Policy
AdWords
We use AdWords to deploy digital advertising on sites supported by AdWords. Ads are based on both AdWords data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AdWords has collected from you. We use the data that we provide to AdWords to better customize your digital advertising experience and present you with more relevant ads. AdWords Privacy Policy
Marketo
We use Marketo to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. We may combine this data with data collected from other sources to offer you improved sales or customer service experiences, as well as more relevant content based on advanced analytics processing. Marketo Privacy Policy
Doubleclick
We use Doubleclick to deploy digital advertising on sites supported by Doubleclick. Ads are based on both Doubleclick data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Doubleclick has collected from you. We use the data that we provide to Doubleclick to better customize your digital advertising experience and present you with more relevant ads. Doubleclick Privacy Policy
HubSpot
We use HubSpot to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. HubSpot Privacy Policy
Twitter
We use Twitter to deploy digital advertising on sites supported by Twitter. Ads are based on both Twitter data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Twitter has collected from you. We use the data that we provide to Twitter to better customize your digital advertising experience and present you with more relevant ads. Twitter Privacy Policy
Facebook
We use Facebook to deploy digital advertising on sites supported by Facebook. Ads are based on both Facebook data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Facebook has collected from you. We use the data that we provide to Facebook to better customize your digital advertising experience and present you with more relevant ads. Facebook Privacy Policy
LinkedIn
We use LinkedIn to deploy digital advertising on sites supported by LinkedIn. Ads are based on both LinkedIn data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that LinkedIn has collected from you. We use the data that we provide to LinkedIn to better customize your digital advertising experience and present you with more relevant ads. LinkedIn Privacy Policy
Yahoo! Japan
We use Yahoo! Japan to deploy digital advertising on sites supported by Yahoo! Japan. Ads are based on both Yahoo! Japan data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Yahoo! Japan has collected from you. We use the data that we provide to Yahoo! Japan to better customize your digital advertising experience and present you with more relevant ads. Yahoo! Japan Privacy Policy
Naver
We use Naver to deploy digital advertising on sites supported by Naver. Ads are based on both Naver data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Naver has collected from you. We use the data that we provide to Naver to better customize your digital advertising experience and present you with more relevant ads. Naver Privacy Policy
Quantcast
We use Quantcast to deploy digital advertising on sites supported by Quantcast. Ads are based on both Quantcast data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Quantcast has collected from you. We use the data that we provide to Quantcast to better customize your digital advertising experience and present you with more relevant ads. Quantcast Privacy Policy
Call Tracking
We use Call Tracking to provide customized phone numbers for our campaigns. This gives you faster access to our agents and helps us more accurately evaluate our performance. We may collect data about your behavior on our sites based on the phone number provided. Call Tracking Privacy Policy
Wunderkind
We use Wunderkind to deploy digital advertising on sites supported by Wunderkind. Ads are based on both Wunderkind data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Wunderkind has collected from you. We use the data that we provide to Wunderkind to better customize your digital advertising experience and present you with more relevant ads. Wunderkind Privacy Policy
ADC Media
We use ADC Media to deploy digital advertising on sites supported by ADC Media. Ads are based on both ADC Media data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that ADC Media has collected from you. We use the data that we provide to ADC Media to better customize your digital advertising experience and present you with more relevant ads. ADC Media Privacy Policy
AgrantSEM
We use AgrantSEM to deploy digital advertising on sites supported by AgrantSEM. Ads are based on both AgrantSEM data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AgrantSEM has collected from you. We use the data that we provide to AgrantSEM to better customize your digital advertising experience and present you with more relevant ads. AgrantSEM Privacy Policy
Bidtellect
We use Bidtellect to deploy digital advertising on sites supported by Bidtellect. Ads are based on both Bidtellect data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bidtellect has collected from you. We use the data that we provide to Bidtellect to better customize your digital advertising experience and present you with more relevant ads. Bidtellect Privacy Policy
Bing
We use Bing to deploy digital advertising on sites supported by Bing. Ads are based on both Bing data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bing has collected from you. We use the data that we provide to Bing to better customize your digital advertising experience and present you with more relevant ads. Bing Privacy Policy
G2Crowd
We use G2Crowd to deploy digital advertising on sites supported by G2Crowd. Ads are based on both G2Crowd data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that G2Crowd has collected from you. We use the data that we provide to G2Crowd to better customize your digital advertising experience and present you with more relevant ads. G2Crowd Privacy Policy
NMPI Display
We use NMPI Display to deploy digital advertising on sites supported by NMPI Display. Ads are based on both NMPI Display data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that NMPI Display has collected from you. We use the data that we provide to NMPI Display to better customize your digital advertising experience and present you with more relevant ads. NMPI Display Privacy Policy
VK
We use VK to deploy digital advertising on sites supported by VK. Ads are based on both VK data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that VK has collected from you. We use the data that we provide to VK to better customize your digital advertising experience and present you with more relevant ads. VK Privacy Policy
Adobe Target
We use Adobe Target to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Adobe Target Privacy Policy
Google Analytics (Advertising)
We use Google Analytics (Advertising) to deploy digital advertising on sites supported by Google Analytics (Advertising). Ads are based on both Google Analytics (Advertising) data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Google Analytics (Advertising) has collected from you. We use the data that we provide to Google Analytics (Advertising) to better customize your digital advertising experience and present you with more relevant ads. Google Analytics (Advertising) Privacy Policy
Trendkite
We use Trendkite to deploy digital advertising on sites supported by Trendkite. Ads are based on both Trendkite data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Trendkite has collected from you. We use the data that we provide to Trendkite to better customize your digital advertising experience and present you with more relevant ads. Trendkite Privacy Policy
Hotjar
We use Hotjar to deploy digital advertising on sites supported by Hotjar. Ads are based on both Hotjar data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Hotjar has collected from you. We use the data that we provide to Hotjar to better customize your digital advertising experience and present you with more relevant ads. Hotjar Privacy Policy
6 Sense
We use 6 Sense to deploy digital advertising on sites supported by 6 Sense. Ads are based on both 6 Sense data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that 6 Sense has collected from you. We use the data that we provide to 6 Sense to better customize your digital advertising experience and present you with more relevant ads. 6 Sense Privacy Policy
Terminus
We use Terminus to deploy digital advertising on sites supported by Terminus. Ads are based on both Terminus data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Terminus has collected from you. We use the data that we provide to Terminus to better customize your digital advertising experience and present you with more relevant ads. Terminus Privacy Policy
StackAdapt
We use StackAdapt to deploy digital advertising on sites supported by StackAdapt. Ads are based on both StackAdapt data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that StackAdapt has collected from you. We use the data that we provide to StackAdapt to better customize your digital advertising experience and present you with more relevant ads. StackAdapt Privacy Policy
The Trade Desk
We use The Trade Desk to deploy digital advertising on sites supported by The Trade Desk. Ads are based on both The Trade Desk data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that The Trade Desk has collected from you. We use the data that we provide to The Trade Desk to better customize your digital advertising experience and present you with more relevant ads. The Trade Desk Privacy Policy
RollWorks
We use RollWorks to deploy digital advertising on sites supported by RollWorks. Ads are based on both RollWorks data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that RollWorks has collected from you. We use the data that we provide to RollWorks to better customize your digital advertising experience and present you with more relevant ads. RollWorks Privacy Policy

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