Neo4J & Google Cloud: Graph Data in Cloud to Address Challenges in FinServ Industry - Build What's Next
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Neo4J & Google Cloud: Graph Data in Cloud to Address Challenges in FinServ Industry

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Neo4j, a leading graph database technology and fully-integrated graph solution on Google Cloud helps today's financial service companies address three significant industry challenges. Read the blog to learn more about Neo4J and Google's partnership!

Over the last decade, financial service organizations have been adopting a cloud-first mindset. According to InformationWeek, lower costs and enhanced scalability were the biggest drivers for cloud adoption in financial services, and cloud-native applications allow access to the latest technology and talent, enabling adopters to rebuild transaction processing systems capable of supporting very high volumes and low latency.

Both Neo4j and Google Cloud have been using relationship-based data representations since the beginning, and we’re dedicated to using this technology to help financial services customers drive business transformation. We are excited about the prospects of financial services (FinServ) cloud systems and believe that graph data in the cloud can help solve significant challenges in the industry.

Data Challenge #1: Risk Management and Compliance

First among the top concerns for any CIO moving to the cloud is risk management and compliance. Disconnected, uncontextualized, or stale data create opportunities for fraud and financial crimes to occur. The fact is when it comes to FinServ, the question is not “if” but rather how often an attack will occur.  Unfortunately, incidents have been trending upward over the last decade, and COVID has only exacerbated this reality. Financial crimes affect the bottom line both in the remediation of these crimes and in intangibles like brand value.  

Add to this the complexity of international banking, which makes “compliance” a moving target. Penalties due to noncompliance are a constant concern to any FinServ organization.

The tabular representation of information with a fixed number of columns that never change prevents a description of an ever changing world with changing characteristics. Relational databases are great if the world you describe does not move fast but have limitations when data structures are highly interlinked and not homogeneous.

Neo4j Aura on Google Cloud provides a foundation for creating dynamic, futureproof, scalable applications that adhere to the security standards and protocols today’s financial services organizations require to meet the challenges of finding and preventing bad actors. This also includes enterprise scalability; reaching over 1 Billion nodes and relationships to streamline queries and provide solutions that meet regulatory and privacy compliance across geographies. Neo4j has helped some organizations save billions of USD in fraud in the first year of deployment alone.  

What makes graph technology the best choice for fraud detection use cases is that the relationships between the data-points are as important as the data-points themselves. Let’s take as an example, one John Smith approaches a multi-national banking institution to manage the primary account for his new holding corporation.  

While no one has any record of John R Smith Holdings LLC, the bank’s application built on graph technology understands that there are several well-known entities owned by John Smith Holdings. The application also identifies several well-known board members who bank with this institution. Due to this relationship-driven approach, the bank now understands John R Smith is not “John Smith,” who previously attempted to open an account for his holding corporation, which had no information associated with it prior to two months ago.

Data Challenge #2 Manual Processes and Inefficiencies 

The ubiquity of the cloud offers an opportunity to deploy automation at unprecedented levels to tackle the errors and inefficiencies that manual processing allows to creep into processes. When data comes from disparate, perhaps legacy systems – which may have become siloed and “untouchable” over the years – further complexity arises. As an example, if someone in sales types “John Smith” into a CRM system not knowing that John R Smith is the spelling in the customer data master, it may result in two separate and potentially conflicting records. Being able to join those records together in a mastered view helps to solve this problem. In addition, low data quality equates to an increase in risk, costs, and implementation times for new systems. 

Neo4j Aura on Google Cloud provides automation and artificial intelligence (AI) that reduces manual processes and the errors that accompany them. In this graph architecture each node, which can represent a person, will have labels, relationships, and properties associated with it. This allows for the use of AI which can easily understand that John Smith in the CRM is the same John R Smith in the customer master. The information contained in Neo4j can be connected bi-directionally to ensure consistency across applications and data sources. 

One of the benefits of this approach is that linking information allows organizations to keep the full value of the data, rather than forcing the data into predetermined tabular representations, with the risk of losing valuable information and insights.

Data Challenge #3: Customer Engagement and Insight

Another significant concern is the high expectations today’s customers have for every interaction. End users are accustomed to predictable experiences on their digital devices, and FinServ apps are no exception. Added to this, the “Covid economy” has driven digital adoption significantly across demographics; even among customers who might traditionally have used in-person services. This also equates to increased expectations for personalized, predictable experiences with every digital interaction. We know that latency has always been a key consideration for financial trading, but a recent ComputerWeekly study showed that every financial organization should ensure their visible latency is at 10 milliseconds or less. Customers no longer accept their broadband is at fault.

Finally, blind spots in the customer journey often result in dissatisfaction, which ultimately leads to increased churn. Without gaining actionable insights from your customers, there is no room to innovate and iterate on what they are looking for in your products and services. And this translates to losing market share and competitive advantage.

The NoSQL architecture, specifically the dynamic schema and structure of Neo4j Aura gives you the ability to take charge of your data and make changes according to your development cycles or newer data models. This equates to faster builds, more comprehensive releases and a wider, richer data-set that can be contextualized and understood instantly. Graph technology is the logical choice for building a Customer 360 application. Under this approach organizations not only get valuable insight into the individual client’s behavior and patterns, but also those of their family, friends and colleagues. This allows for stronger personalization, targeted campaigns and successful execution, resulting in increased customer satisfaction and retention levels.

Graph Technology on Google Cloud

Neo4j.jpg
Neo4j can help analysts visualize which accounts have shared attributes, making it more likely that they have the same high risk owners.

Neo4j is a recognized leader in graph database technology and the only fully integrated graph solution on Google Cloud, helping to fill a common need for Google Cloud customers. Both Neo4j and Google Cloud are invested in continuing to grow our partnership and mutual product direction.  

You can find and deploy the Neo4j graph database straight from the Google Cloud marketplace, whether you want to download the software for an on-premises deployment, use the virtual machine image, or use the hosted solution, Aura on Google Cloud, the graph database-as-a-service. In any deployment, you get the same enterprise-grade scalability, reliability, and connectivity along with successful, repeatable use cases you can rely on to resolve your particular challenges and integrated billing. 

For a real-world example of how graph technology can optimize financial services, you can read our Case Study with fintech Current. Current, a leading U.S. financial technology platform with over three million members, used Neo4j Aura on Google Cloud to create a personalization engine based on client relationships. 

To learn more about Neo4j Aura on Google Cloud for FinServ organizations, register for our webinar on Thursday, December 16 with Jim Webber, Chief Scientist, CTO Field Ops at Neo4j and Antoine Larmanjat, Technical Director, Office of the CTO, Google Cloud. 

Click here to Register

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Go Green with Google’s Latest Tool and Pick the Most Sustainable Cloud Region

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Google's sustainability initiative to turn carbon-free by 2030 is followed by the release of its latest tool. The tool helps pick a cloud region, taking into consideration variables such as price, latency and lowest CO2 levels.

As a Google Cloud customer, your carbon footprint is already carbon neutral: Google first achieved carbon neutrality in 2007, and has been purchasing enough solar and wind energy to match 100% of its global electricity consumption since 2017. Now, Google is targeting a new sustainability goal: operating on carbon-free energy (CFE) 24/7, everywhere, by 2030. 

We want to empower you to make more sustainable decisions and progress with us towards this 24/7 carbon-free future. Earlier this year, we published the carbon characteristics of our Google Cloud regions. Later, we introduced a simple tool to help you pick a Google Cloud region, taking variables like price, latency and sustainability into account. Our next question was: what’s the best way to surface that sustainability info when you’re actually picking a region for your cloud resources? 

Starting today, we are indicating regions with the lowest carbon impact inside Cloud Console location selectors. Available today for Cloud Run and Datastream, you’ll see it roll out to more Google Cloud offerings over time:

Cloud Run region selector.jpg
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Regions that feature the “Lowest CO2” and the leaf have a CFE% of at least 75%, or, if the information is not available for this region yet, a grid carbon intensity of maximum 200 gCO2eq/kWh. You can read more about how we calculate these metrics in our documentation.

Before releasing this feature, we ran experiments to measure its impact: Users who were exposed to the enhanced region picker were 19% more likely to select a “low carbon” region for their Cloud Run service—a significant lift. These results show that by displaying carbon information in context of when you make the decision of picking a region, we are helping you make more sustainable decisions.

By sharing and displaying carbon information of Google Cloud regions, together we’re making tangible progress towards our goal of a carbon-free future. Learn more about Carbon free energy for Google Cloud regions.

Case Study

Payhawk Becomes a Unicorn with Google Cloud-Powered Automated Financing Software

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Payhawk, the provider of automated financing software, has reached unicorn status thanks to its integration with Google Cloud. The company's platform streamlines financial processes and offers businesses valuable insights into their finances.

For far too long, managing employee expenses has been a time-consuming process that requires manual data entry and reconciliation to bridge the gap between business bank accounts and ERP systems. In the absence of an integrated workflow, finance teams use multiple systems to manage credit card and cash payments, and finding receipts. In most cases, they also lack real-time visibility into company spending.

The complexity grows exponentially as businesses expand, especially into new regions. Extra administration required to manage new bank accounts, card issuers, and local accounting systems impedes decision making and negatively impacts revenues and growth. Businesses of all sizes struggle with this, but it can be especially challenging for medium to large enterprises.

Payhawk set out to help businesses overcome these challenges when we founded the company in 2018. We combine VISA company cards, reimbursable expenses, and accounts payable into a single product. Our customers can automate manual processes, maximize efficiency, and accelerate business expansion.

Payhawk founders Konstantin Dzhengozov, Boyko Karadzhov, and Hristo Borisov

Setting up our first cloud cluster in less than a week

To support growth and attract investment we were keen to launch our solution on a scalable, future-proof IT architecture that didn’t require extensive technical support. This is where Google Cloud made a big impression, especially the user interface and documentation which massively reduces the resources required to set up clusters and put them into production.

I’m a CTO, not a DevOps specialist, but in less than a week I was able to set up a secure, reliable operating infrastructure. This enabled us to fast-track our application development and we were able to issue our first card in just eight months. Our Google Cloud partner, Cloud Office also gave us valuable assistance, guiding us through the deployment process and advising on Google Cloud’s extensive range of solutions.

Google Kubernetes Engine (GKE) played a critical role, accelerating the deployment and management of our cloud native applications. We use Cloud SQL as our database while other important tools include Cloud Memorystore, Vision AI, Cloud Storage and Artifact Registry for our wider data storage and application needs. With Firebase we’ve been able to build a notification system for mobile devices.

Another incentive is that most other cloud solutions require add-on services to build and keep your product live. With Google Cloud, all the services that Payhawk needs including logging, metrics, monitoring of resources, and utilization of CPU memory come as standard.

For instance, I was really impressed by Google Cloud’s operations suite, which includes Cloud Logging and Cloud Monitoring. If there are any anomalies in our cloud architecture, we can track and resolve them with minimal disruption to our operations. This also removes the need to invest in an additional observability solution.

Reliability that builds customer trust

Google Cloud also supports Payhawk’s mission to put customers at the center of our organization. Thanks to Google Cloud error reporting and tracking and Google Cloud single sign on, Payhawk’s engineering team can anticipate customer issues and correct them in less than one hour. Trust is everything, and Google Cloud gives us the tools to boost customer satisfaction and build long-term relationships.

As a young business, managing costs is also a priority. The Google for Startups Cloud Program, which includes credits for Google software and tools, enabled us to push the business forward without having to worry about financing our infrastructure, especially in the first year. This gave us breathing room to work through funding, application development, and the onboarding of our first customers.

In addition, Google Cloud gives us confidence that we can grow the business fast. In most months we have seen more than 10% growth — in some cases it’s been 20%. In the first half of 2022, the business doubled in size, but Google Cloud gave us the flexibility to scale our infrastructure, adding storage, memory, and processing power as we onboarded new customers. The pricing model is also generous so that we can grow our revenues while keeping control of operational expenditure.

Since launch we have acquired a valuable mix of customers from startups to large businesses that want to reduce the costs of their expenses programs and increase employee satisfaction. They include ATU, a German automobile servicing company, which has successfully digitized its entire procurement process, and Discordia, a Bulgarian logistics business with 10,000 trucks, which has issued Payhawk cards to all its drivers.

Looking to the future, it’s no exaggeration to say that Google Cloud is a foundation of our business and has given investors confidence in our operations. From a first seeding round of €3 million, early this year we closed a Series B extension of $100 million. This gives us a valuation of $1bn and makes Payhawk the first ever Bulgarian unicorn.

We now operate in 32 countries in Europe and the US, and plan to double our team by the end of the year. It feels like we’ve come a long way since we first started using Google Cloud, and I’m thrilled that we have Google Cloud as a global technology partner supporting our mission to transform expense management and financial operations worldwide.

Payhawk team members

If you want to learn more about how Google Cloud can help your startup, visit our page here to get more information about our program, and sign up for our communications to get a look at our community activities, digital events, special offers, and more.

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Accelerating Success: Tips and Techniques for Optimizing and Scaling Your Startup

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Maximize the impact of your startup by learning from the Build Series. In this series, we'll cover the key elements of growth and show you how to optimize and scale your business for success. Read more.

At Google Cloud, we want to provide you with the access to all the tools you need to grow your business. Through the Google Cloud Technical Guides for Startups, leverage industry leading solutions with how-to video guides and resources curated for startups.

This multi-series contains 3 chapters: Start, Build and Grow, which matches your startup’s journey:

  • The Start Series: Begin by building, deploying and managing new applications on Google Cloud from start to finish.
  • The Build Series: Optimize and scale existing deployments to reach your target audiences.
  • The Grow Series: Grow and attain scale with deployments on Google Cloud.

Additionally, at Google we have the Google for Startups Cloud Program, which is designed to help your business get off the ground and enable a sustainable growth plan for the future. The start of the Build Series delineates the benefits of the program, the application process, and more to help your business get started on Google Cloud.

A quick recap of the Build Series

Once you have applied for the Google for Startups Cloud Program, there’s so much to explore and try out on Google Cloud.

Figuring out a rapid but solid application development process can be key to many businesses in reducing time to market. Furthermore, learning what database to use to handle application data can be tricky. Deep dive into our Firestore video which walks through how Firestore can help you unlock application innovation with simplicity and speed.

We then move on to a deep dive into BigQuery and how it can help businesses. BigQuery is designed to support analysis over petabytes of data regardless of whether it’s structured or unstructured. This video is the goto video for getting started on BigQuery!

If you are someone looking to run your Spark and Hadoop jobs faster and on the cloud, look to Dataproc. To learn more about Dataproc and how this has helped other customers with their Hadoop clusters, click the video below to learn all things Dataproc related.


Next, we find out what Dataflow can bring to your business; some advantages, sample architectures, demos on the console, and how other customers are using Dataflow.

We also talked about Machine Learning, starting from selecting the right ML solution to Machine Learning APIs on cloud to exploring Vertex AI. Following that we look into API management in Google Cloud and how Apigee helps operate your APIs with enhanced scale, security, and automation.


We ended the series with the last two episodes focusing around security deep-dive and using Cloud Tasks and Cloud Scheduler.

Coming up next – The Grow Series

Dive into the next chapter of this multi-series, with our upcoming Grow Series, where we will be focusing on growing and attaining scale with deployments on Google Cloud.

Check out our website and join us by checking out the video series on the Google Cloud Tech channel, and subscribe to stay up to date. 

See you in the cloud!

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VMware Engine’s Exciting New Updates: A Google Cloud Journey

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Discover the exciting new updates and features in Google Cloud's VMware Engine, enhancing your ability to migrate and operate vSphere workloads efficiently in a cloud-first, enterprise-class VMware environment on Google Cloud. Learn more...

IT leaders today are being asked to simultaneously support their company’s infrastructure, find opportunities for growth, and meet their goals with fewer resources and smaller budgets than before. Recently we highlighted three customers who are leveraging Google Cloud VMware Engine to achieve these goals while lowering their TCO and transforming their organization. 

It’s because of these successful customer outcomes that we have been awarded the 2023 VMware Cloud Innovation and SaaS Transformation partner achievement award for delivering solutions that accelerate customers’ digital transformation journey. We’re honored to receive this award and continue to stay focused on delivering tremendous value to our customers.

In the past few months, we’ve also made several updates to Google Cloud VMware Engine. Today’s post provides a recap of the latest milestones that make it easier for you to migrate and run your vSphere workloads in a cloud-first, enterprise-class VMware environment in Google Cloud. 

Back in September 2022, we announced a number of updates including the preview of API/CLI support (which is now available). In February 2023, we also talked about how to use NetApp CVS as datastores for VMware Engine.

Key updates this time around include:

Availability of VMware Engine in DelhiSantiago and Milan regions: This brings the availability of VMware Engine to 17 regions worldwide, each supporting 4 9’s of uptime SLA for clusters 5 or more, serving the needs of our regional and multi-national customers. In addition, we have also added a second zone in the London region.

Filestore datastore support for VMware Engine: Generally Available in all VMware Engine regions, you can use Filestore High Scale and Enterprise tier instances as external NFS datastores for VMware Engine nodes. Filestore is VMware certified as an NFS datastore with VMware Engine. You can size compute and storage capacity independently to meet your workload requirements for your storage-intensive VMs. You can also leverage vSAN for low-latency VM requirements and scale Filestore from TBs to PBs for the capacity hungry VMs. If interested in this feature, please contact your Google account team.

Stretched private clouds: These private clouds stretch across two data zones and a witness zone all within the same Google Cloud region. Stretched private clouds use vSphere and vSAN stretched clusters to provide compute and storage high availability against zone-level failures. This capability is now available in Frankfurt and Sydney regions. Learn more here.

Zerto solution version 9.5u1 support: This recovery solution allows critical infrastructure and application virtual machines (VMs) to be replicated continuously from your on-premises vCenter to your private cloud. Learn more about setting up Zerto here.

Google Cloud Backup and Disaster Recovery (GCBDR): GCBDR is available to protect applications running in VMware Engine, and can be managed within the Google Cloud Console. We recently launched GCBDR under Google Cloud Platform Terms of Service simplifying customers’ purchasing and support experience. 

vTPM support: Google Cloud VMware Engine private clouds now support the addition of a Trusted Platform Module (TPM) 2.0 virtual cryptoprocessor to a virtual machine. You can add vTPMs to VMs by following VMware instructions or upgrading your existing VMs to include a vTPM. You can read more about this in the VMware blog.

This brings us to the end of our updates this time. For the latest updates to the service, please bookmark our release notes.

Case Study

Marxent Leverages Google Cloud to Elevate Customer Journeys on Retail Apps with 3D Shopping Experiences

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3D Room Commerce company, Marxent leverages Google Cloud to help the largest retail and home goods companies build unique customer journeys by helping buyers visualize products in the context of their home floor plan in a single click! Learn how.

As ecommerce for home goods exploded in popularity during COVID, furniture and DIY retailers looked to find new ways to grow online transaction sizes to in-store levels. Shopping for furniture and home improvement projects has always been challenging online. Furniture, kitchen cabinets, fixtures, and appliances become a part of daily life, are challenging to return, and have a low purchase frequency. Once a shopper makes a decision, they tend to live with it for many years. These are visual, tactile, decisions that require measurements, style choices, budgeting, an understanding of available products, and an involved consideration processes. During the pandemic, retailers turned to 3D to enhance these virtual shopping experiences. 

Inspiration and visualization cultivate confidence

Our 3D Room Commerce company, Marxent offers 3D visualization and configuration solutions that help retailers sell complex, configurable products online through consumer-facing 3D design and visualization apps. The Marxent 3D Room Planner with HD Renders helps shoppers to visualize how furniture or kitchen cabinet configurations will look in the specific floorplan of their home. Founded in 2011, Marxent envisions a world where buying a dining table or remodeling an entire kitchen is as easy as buying a car from Carvana or ordering dinner through  Bite Squad. Our 3D apps create a streamlined inspiration to transaction to advocacy model that cultivates shopper confidence and allows retailers to sell the whole room, not just individual items. 

Using Google Cloud as a foundation, we help some of the largest retail and home goods companies in the world provide exceptional customer journeys. We trust Google Cloud because our clients trust us to make it faster and easier for shoppers to buy semi-custom, configurable projects.

Embracing the power of 3D to super-charge ecommerce 

It’s inarguable: e-commerce is on the rise. More people than ever before are shopping online for furniture, kitchen cabinets, decking, and other large-scale configurable products. 

Customers who design with a retailer, usually buy from them. When shoppers visit stores and showrooms, they find inspiration in merchandised scenes that illustrate how products like sofas, chairs, rugs and lamps work together to accomplish a look. Skilled sales people make suggestions and offer advice on how to put pieces together. They may even work up a quick floor plan to show how multiple items work together in a room. In store, the inspiration phase is intimately tied to consideration and, ultimately, to driving transactions.

By contrast, online shoppers typically start home projects by seeking inspiration and ideas from Pinterest, Instagram and unbranded online image searches. Once they have formed their style preferences, shoppers keep searching to compare products across multiple retailers, plan their project, and put together a final budget. 

To own the whole project sale, retailers need to own the entire inspiration to transaction to advocacy journey. With both online and in-store applications, Retailers leverage Marxent’s 3D Room Planner app to build shopper confidence, capture the whole room sale and win the customer over.

https://youtube.com/watch?v=_svOdVvX5LA%3Fenablejsapi%3D1%26

PRE-RENDERED MID-POLY 3D SCENE

PRE-RENDERED.jpg
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POST-RENDERED MID-POLY 3D SCENE – This is a slightly different angle of the same room that has been rendered into a “Raw Render” (rendered in under 2 minutes).

POST-RENDERED.jpg
Click to enlarge

Through Marxent’s 3D Room Commerce solution, users experience a cyclical inspiration to transaction to advocacy journey. It starts with shoppers viewing inspirational images and media online. Using Marxent’s applications, they can design directly from inspirational images to create a custom, configured space without any product catalog knowledge. Shoppers can visualize the products they love together and in the context of their own floor plan instead of navigating product pages and wondering if items will work together. 

Then, they can add the whole room to a shopping cart with a single click. While this virtual experience does lead to a transaction, it also allows users to save, collaborate on, and share the spaces they’ve created. They become advocates by sharing their projects on social media, starting the inspirational content cycle again. 

Putting an end to manual operations

To deliver renders at scale, Marxent needed to update their cloud render solution. Initially, our 3D Art team operated a manual on-premise render fleet. However, this required many hours of manual setup, configuration, and operation. We also had to manage expensive graphics servers—bare metal, CPUs, GPUs, RAM, HDD, and more. The only solution was to automate the 3D rendering process and empower end-users to rapidly create their own 3D room renders. 

When we were evaluating new solutions, we saw distinct advantages in the Google Cloud Platform that would help them safely and securely scale their business, while strengthening their partnerships with end customers. For example, in moving to Google Cloud, we could automate and scale our rendering process without having to manage fleets of physical servers. We also viewed the platform as an asset due to Google’s secure-by-design infrastructure, agility, data analytics capabilities, and potential for joining the Marketplace.

Creating magical customer experiences that inspire purchase

To provide our customers and shoppers with contextual experiences, Marxent’s applications use mid-poly 3D models that balance speed and realism. These models provide a latency-free, real-time design experience that can be rendered into scenes that are realistic enough to be perceived as photos on social media. 

The complex process of rendering these images requires a combination of efficiency, speed, analytics, and consistent performance that Google Cloud provides. When configured with powerful and speedy gaming GPUs, Marxent can provide fast rendering that meets customers and shopper demands. Here’s a look at our HD Renders application.

HD Renders application.jpg
Click to enlarge

Before a user can request an HD Render, they must create a room in the Marxent 3D Room Planner. Once requested, Marxent pulls the saved project from the database and kicks off the process with Cloud Pub/Sub. The project loads into a gaming GPU, using the same platform code running when the user first creates the room in the application. It boots up the app in the cloud to load the room.

The code then scours the space and prepares it for rendering, adjusting texture formats, and adding in lighting. After going through the render engine, the project automatically uploads to Cloud Storage. Finally, the user receives a link to the final product. Throughout, Cloud Pub/Sub handles messages ensuring the right event processes are happening, such as rendering success or failure.

Using this process, it’s possible to create dozens of images out of a single scene, trading products in and out of a floor plan by leveraging a complete catalog of content geometries and covers, textures, and finishes.

Utilizing Google Cloud throughout the buying journey 

Today, Marxent’s applications power world-class retailers with AR, VR, and 3D commerce experiences. We use cutting-edge graphics hardware to create renderings in less than 2 minutes per screenshot, often much faster. We’re also saving money as we no longer have to manage expensive servers or purchase expensive hardware upfront. Our clients are happier because we have passed on the cost savings to them while now having limitless scaling capabilities to meet demand.

By partnering with Google Cloud, Marxent can confidently offer our customers secure applications built on infrastructure with advanced security tools that support compliance and data confidentiality. Backed by a globally consistent platform, we can also help brands build reliable purchasing experiences across customer touchpoints—without fear of downtime during peak sales periods. This strategic partnership has allowed us to provide a best-in-breed, customer-first experience that our customers demand while providing the reliability that our partners expect.

With customers demanding seamless shopping experiences, Marxent’s 3D technologies open doors to new, easier, more convenient, and more satisfying shopping experiences that empower consumers to buy the right products the first time. 

If you want to learn more about how Google Cloud can help your startup, visit our Startup Program application page here and sign up for our monthly startup newsletter to get a peek at our community activities, digital events, special offers, and more.

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