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Cubic Inch, an engineering and manufacturing company based in Warsaw, Poland, faced a significant challenge in their quoting process. The process was time-consuming and required a substantial amount of data collection from potential customers before a price could be determined. This included receiving a file to determine the part’s size, volume, and other dimensional information, as well as identifying the part’s orientation and other factors that could impact production. Additionally, customers had to provide other specifications such as material and quantity of parts to be quoted. The company also required contact and other business-based information. Collecting all this information often involved a series of phone calls or back-and-forth emails. Once a customer was ready to place an order, additional information such as payment and shipping methods had to be communicated. In a manual environment, much of this was handled with spreadsheets and other disparate software, leading to duplicate work and confusion.

General Pattern, a prototype, tooling, and rapid manufacturing company, faced a challenge when one of its clients from the consumer products industry required a more efficient, faster, and cost-effective method for creating prototypes and end-use parts than traditional manufacturing methods. The company decided to invest in HP’s Multi Jet Fusion (MJF) 3D printing technology, which led to a surge in orders. This influx of orders necessitated a more efficient way to manage front-end processes like quoting and order entry. General Pattern sought a software solution that was easy to use, minimized staff training, and was familiar with the nuances of HP’s technology to develop accurate and competitive pricing models.

iOrthotics, an Australian firm that develops custom devices for the medical industry, faced a challenge in effectively reaching and serving new customers in different markets. The company had invested in HP’s Multi Jet Fusion 3D printing technology and created a spin-off, i3DPS, to serve smaller companies who couldn’t justify the investment in equipment and talent. However, the traditional business-to-business (B2B) eCommerce approach was proving to be a hurdle. Most B2B companies, including service bureaus and machine shops, had websites that were more informative than transactional. The existing online quoting systems were often cumbersome, involving open-ended forms and back-and-forth conversations between the estimator and the customer. This not only frustrated customers but also limited the amount of work each estimator could complete, prohibiting the shop from reaching its capacity. iOrthotics recognized these limitations and was determined to eliminate them.

MakeItQuick, a UK-based additive manufacturing service bureau, faced a significant challenge in its early stages. The company was spending an excessive amount of time and resources on manual tasks such as quoting and order management. Each quote took anywhere from 10 minutes to over an hour to prepare, costing the company an average of £15.00 per quote. Additionally, pushing each order through its facility cost between £15-20.00. This redundant work was not only costly but also hindered the company's ability to scale effectively. The team at MakeItQuick realized that to grow, they needed to eliminate much of this redundant work.

Skillcraft Agencies, a brand-specific hardware wholesaler, was grappling with the challenges of a warehouse that primarily operated on manual systems. The lack of ability to perform cycle counts led to inaccurate stock information and extensive inefficiencies in the warehouse. This significantly impacted the company's drive to increase revenue and reduce costs without expanding its workforce. The manual, time-consuming tasks were hindering the company's progress towards increased efficiency and the annual stocktake was a lengthy process with a high stock variance.

Creating high-quality training data for machine learning (ML) use cases can be expensive and time-consuming, especially for specialized fields that require domain experts to review and label the data. This is particularly true in the medical field, where doctors are often required to meticulously label or review training data. This process can be arduous and costly, slowing down the development of potentially life-saving algorithms. The challenge was to find a way to create high-quality training data with less involvement from physicians, thereby reducing costs and speeding up the development process.

Creating high-quality video content, such as movies, video games, or live broadcasts, is typically expensive and requires top-notch equipment and animation talent. Traditional technologies for motion capture data collection require markers, which can be bulky, costly, and struggle to capture detailed data. Move.ai, an emerging AI company, aimed to make processes like motion capture and key point recognition easier, faster, and less expensive for both individuals and studios. However, their markerless motion capture solution and AI depth keying tool presented unique challenges when training their AI models. They needed to train algorithms to track a target across keyframes, identify that person or object, identify the people and objects that come into contact with this target, and extract the spatial data of the area captured within the frame.

FARFETCH, a global platform for luxury fashion, faced a significant challenge when Google introduced Core Web Vitals (CWV) in 2020. These user experience metrics became a guiding light for the FARFETCH engineering team, as improving CWV meant that a site would load faster and be easier to interact with. Two of the most important CWVs for FARFETCH were Largest Contentful Paint (LCP), which measures the time it takes to display the largest content on the site, and Time to Interactive (TTI), which measures the time it takes for a site to become fully interactive for the user. The complex architecture of third-party services made it difficult for FARFETCH to identify opportunities for performance improvement.

Founded in 2015, Getir is an ultrafast delivery pioneer that has expanded its unique business model over time with various services. The company revolutionized last-mile delivery to customers with a 10-minute grocery delivery proposition, offering approximately 2,000 everyday items. Getir is now operating in all 81 cities of Turkey and launched operations in a number of countries in 2021. The company’s tech has enabled it to scale and succeed under the most challenging of circumstances. However, the company's proposition is speed through technology, and the end-to-end delivery process, from order to courier, must be fast and seamless. This requires a robust, cloud-based, integrated technology system that uses data and algorithms to manage supplies and customer demand.

Indonesia-based healthcare company, Halodoc, was founded in 2016 to address a significant problem in Indonesia: a severe shortage of doctors for its population of over 270 million people. The scarcity of healthcare professionals was further exacerbated by the uneven distribution of doctors across the country. Halodoc's health-tech platform aimed to bridge this gap by connecting patients with licensed doctors, hospitals, pharmacies, insurance providers, and labs through a single platform accessible via mobile or web application. However, the COVID-19 pandemic led to an unprecedented surge in demand for virtual health services. The technology team was faced with the challenge of delivering optimal customer experiences with high uptime and reliability, while managing the increased system load.

HealthifyMe, a health and fitness app based in India, was facing a significant challenge in managing its growing user base, particularly during peak periods such as after Diwali, Christmas, and the New Year. The app, which has over 35 million downloads and 1500-plus nutrition, fitness, and yoga coaches, was experiencing a two to three times spike in traffic during these periods, causing a tremendous system load. Additionally, the company was also dealing with the challenge of streamlining COVID-19 vaccination bookings when the government rollout was launched for people in India under the age of 45. The booking slots were in short supply, and the team needed to build a feature that would allow people to find nearby vaccination slots with ease.

HT Digital Streams (HTDS), one of India’s fastest-growing digital media companies, serves around 250 million users every month across all its platforms. The company powers several of India’s leading news brands and is part of a rapidly evolving and highly competitive digital media and entertainment sector. The tech team at HTDS is tasked with delivering on wider business and core business metrics, monitoring performance, and addressing any technical issues. However, they faced significant challenges in measuring the impact of technology performance on business metrics such as revenue and profit, and correlating tech and strategic KPIs. The team also struggled with lost support tickets and issues falling through the cracks, which hindered their operational efficiency.

Intelligent Growth Solutions (IGS), a company that grows nutritious food via automated growth towers, faced a significant challenge in maintaining the reliability of their system. The nature of their product demanded a high degree of reliability, as any outages could lead to the death of their crops. As a small organization, they needed insight into the system's reliability, especially as they scaled and handled larger volumes of data. Initially, they used Application Insights as a part of Microsoft Azure, but it wasn't well integrated with the amount of data they gathered due to their heavy use of Kubernetes. They considered open source solutions, but with only three people on the team, managing that would have turned into a full-time job. They needed a SaaS solution that adhered to open standards, allowed monitoring with logging and tracing, and was Kubernetes-native.

Kmart, one of Australia's largest retailers, was facing a challenge in its digital transformation journey. Despite having a strong physical presence with 84% of Australians living within 10km of one of its stores, Kmart was keen on investing in its digital business to strengthen its market-leading and personalized omnichannel experience. The company was looking for ways to improve operational efficiencies and deliver greater value for customers by investing in data and technology. In 2020, Kmart commenced a re-platforming process, which included assessing existing infrastructure and systems and sourcing new solutions to support and facilitate its digital evolution. The main goal was to deliver peak performance across online and in-store point of sale (POS) systems, improve system resilience, and enhance customer experience. Additionally, Kmart wanted to improve visibility as the company did not have reliable data about how their website was being accessed, or the purchase journeys their customers were taking.

Kogan.com, a leading Australian consumer brand, experienced a significant surge in demand during 2020. The company's share price rose by 360% between March and July, and gross sales increased by nearly 40% to reach AUD$768.9 million. This was largely due to the increased demand for online shopping during the pandemic, with consumers seeking technology, home entertainment, PPE, office supplies, and exercise equipment. While Kogan.com was able to keep up with the demand, other online retailers began to experience website crashes or slowdowns. Kogan.com's challenge was to manage this surge in demand while maintaining its strong infrastructure, stock reordering initiatives, and forecasting. The company also needed to manage the growth of its customer base, which was rapidly expanding.

GE Digital was faced with the challenge of managing storage in the rapidly evolving container technology ecosystem. The company was using Cloud Foundry, which was effective for stateless applications, but they needed a solution that could handle both stateless and stateful applications. They were looking for a solution that could provide a single infrastructure that would allow them to run both stateless and stateful applications. They also needed a solution that would support encryption and snapshotting out of the box, which are crucial for an industrial company. The challenge was to find a solution that would not only meet these requirements but also be cloud-agnostic and provide a uniform experience for their DevOps teams.

Pyvotal Solutions, a cloud-based infrastructure and platform services company, was faced with the challenge of building platform solutions for cost-conscious, yet demanding customers. The company needed to provide a reliable, high-performance platform using fewer resources. The majority of their customers required a complete managed solution for their applications, such as e-commerce sites, without wanting to manage the infrastructure or the CMS. Additionally, they needed a solution that was agile and cost-effective. Traditional virtual machines were not efficient as they required a dedicated resource per application, leading to underutilization of resources during certain times of the day. Furthermore, the company faced challenges in running stateful services on containers, particularly in managing persistent storage.

Software Motor Company (SMC) was founded in 2013 with the mission to bring the benefits of the Internet of Things (IoT) to electric motors. The company developed a radically more efficient electric motor that could save enormous amounts of energy globally. However, the company faced several challenges. The electric motor industry had seen little innovation over the past 40 years, with induction motors being the standard. These motors were inefficient in terms of energy consumption and often ran at a fixed speed, consuming 100% electricity even when they only needed 20% to generate the right amount of torque. Variable frequency drive (VFD) motors managed to consume electricity more intelligently, but the components involved in VFDs were expensive, inefficient, and often broke. This forced buyers to choose between energy efficiency, upfront cost, reliability, and ongoing maintenance cost. SMC needed a solution that would address these issues and deliver multiple related benefits.

WCG Solutions, a defense contractor based in San Diego, was facing significant challenges with their infrastructure. The company provides services for government customers, including the Navy and the Department of Defense, and is involved in building and maintaining a suite of web-based collaboration tools. These tools are designed to facilitate communication across research and development organizations within the government. However, the company was struggling with the overwhelming technical debt of poor configuration management. This led to issues such as not knowing which deployments were configured in which way, making updates very difficult. Additionally, the company was dealing with the problem of having to rely on configuration management at the system level, which was not efficient or effective. The company was also facing challenges when it came to deploying stateful services in containers. Most of their services required persistence, and the push towards immutable infrastructure made it difficult to ensure that no one host was critical to their infrastructure.

Borchers, a Milliken & Co. company, is a global manufacturer and leading supplier of coating additives and specialty catalyst solutions. With technical service teams in the US, Germany, and China, Borchers faced the challenge of meeting constantly changing customer needs while adhering to increasingly stringent environmental regulations and specific market demands. The company prioritized quick response times and effective collaboration both within and outside of the organization. However, the lack of a unified system for application development and testing posed a significant challenge. The company needed a solution that could streamline data capture at each step of the process, from opportunities and projects to formulations, testing, analysis, feedback, and beyond.

Chemstar, a provider of environmentally friendly, high-performance starch-based polymers, was faced with the challenge of accelerating their new product development and expanding into new applications. To achieve this, they needed to shorten their new product development process and expand their R&D and sales teams. The company was also looking to digitize their project workflows and implement a data-driven project scoring process. The goal was to track the entire process, from a new customer request through product development and delivery, and to provide quantified insights into the end-to-end process. This would enable executives to continuously improve the innovation process and make informed decisions about which projects to pursue.

Circle-Prosco, Inc. (CPI), a provider of custom metal finishing formulations to aluminum and automotive manufacturers, was facing challenges in managing its sales, technical service, and lab work. The company had been experiencing aggressive growth, which led to a significant expansion of their sales, R&D, and quality teams. However, their existing stand-alone CRM system was unable to interface with the lab or support CPI's technical process. This lack of integration resulted in a lack of shared visibility of sales opportunities, lab projects, and customer feedback among the sales, technical service, and lab teams. Additionally, the process of generating sales quotes was time-consuming, taking up to 4 hours for each quote.

DCL, a leading technical service provider, was facing challenges in managing its technical service and quality control cycles. The company was struggling with time-consuming data reentry, duplication of lab work, and inefficient management of lab tests and work. The technical service team was finding it difficult to quickly turn around requests from sales and provide comprehensive reporting for all projects completed in its U.S. technical center. The existing process involved capturing all formulation and test data manually, which was not only cumbersome but also prone to errors. Moreover, the data was stored in spreadsheets and hard-to-find files, making it difficult to access and analyze when needed.

Hauthaway, a company with a rich history dating back to the mid-1800s, has always been at the forefront of innovation and reinvention. Over the years, the company has evolved from manufacturing protective coatings for leather shoes to producing polyurethane polymers and compound finishing materials for various industries including automotive, biomedical, construction, maintenance, and textile. However, the company faced challenges in managing its chemistry innovation process. Weekly meetings required pulling information from four different systems, which was a time-consuming and inefficient process. Moreover, valuable past formula, test, and technical data were trapped in paper notebooks and were rarely referenced. This meant that chemists often had to start from scratch for every new project. Additionally, the onboarding process for new chemists was slow as they had to navigate through disparate systems and data sources.

Magni, a leading provider of protective coatings for various applications, was facing challenges with its back-end formulation development process. The process was managed using a combination of Excel and Deacom ERP, and their project management systems were based on SharePoint. This setup was not efficient and lacked real-time visibility into the latest product and project information for their worldwide team of experts. In 2020, Magni decided to modernize its back-end formulation development process and replace their SharePoint-based project management systems. The challenge was to integrate all R&D formulation development and Tech Service projects into a unified system that would provide real-time visibility and streamline operations.

Origin by Ocean, a company developing core biorefining technology to extract value from marine biomass, had the opportunity to set up a brand-new lab in September 2020. The challenge was to ensure that all their detailed R&D data was captured digitally, reusable, and AI-ready from day one. Dr. Mari Granström, the Chief Science Activist and Co-founder of Origin by Ocean, had previous experience with labs conforming to software, which often led to inefficiencies and misalignments with the company's vision and goals. She was determined to find a solution that would fit the company's vision and goals in terms of lab best practices, rather than the lab having to adapt to the software.

Vibrantz, a company known for its commitment to constant improvement and exceptional customer service, was facing challenges in tracking projects, formulas, materials, testing, and feedback for their new development and technical service requests. The company was using outdated Sharepoint and Biovia lab notebook systems, which were not efficient enough to meet their growing needs. The technical service teams were handling thousands of color match requests and related lab work each year, but the process of capturing all formulation and test data was cumbersome and time-consuming. The company was also struggling with automating calculations, process steps, and approvals to speed up the end-to-end tech service process.

Adaptive Corporation, a leading Digital to Physical Product Lifecycle Company, was facing significant challenges with its High-Performance Computing (HPC) system. The company's workload varied greatly throughout the year, leading to either underutilized computing capacity or insufficient capacity when multiple projects were underway simultaneously. This resulted in bottlenecks when multiple jobs needed to be solved at the same time, causing projects to run over schedule. Additionally, the on-premise hardware was becoming outdated within 2-3 years, necessitating frequent upgrades and a dedicated IT support team to maintain the servers and licenses. These issues were undermining Adaptive Corporation's mission to provide tailored solutions that help customers shorten development and production cycles.

American Axle & Manufacturing, a leading global Tier 1 automotive supplier, was facing challenges with their simulation needs. They use computational fluid dynamics to simulate the lubrication process, aiming to optimize the way oil goes onto bearings or gears inside their products. These simulations are complex and require significant computing resources. Their models required anywhere between 32 to 150 cores to run, dictating the size of the server needed. Before using Rescale, they had a single server with 64 cores. The main challenge was the scalability of hardware requirement. To optimize a specific axle, they needed to conduct several runs, which could be different angles of inclination of a moving car or an SUV driving at different speeds. Depending on how soon they needed an answer, they might want to run a number of these jobs simultaneously, instead of waiting to run them one by one.

Bombardier Aerospace, a global leader in aviation product design, manufacturing, and support, was seeking to demonstrate the viability and superiority of industrial-scale simulation in the cloud for both large and small companies across most engineering and scientific applications. The project involved the setup and simulation of unsteady airflow around aircraft landing gear, a complex task requiring significant computing capacity and specialized software. The challenge was to provide a platform that could handle the computational demands of the project, while also being user-friendly and accessible. The project was conducted in conjunction with the HPC Experiment organized by Ubercloud, using open-source data and simulation tools exclusively.