Zillow Group, the owner and operator of the largest online real-estate and home-related brands, was struggling to provide timely and accurate home valuations, known as Zestimates, for all new homes. The company's in-house machine-learning framework, which ran on-premise to process vertically scaling workloads, was unable to scale fast enough to meet the growing amount of data and the increasing complexity of machine-learning models for accurate Zestimates. The company specifically sought a distributed platform, which would enable the fast creation and execution of massively parallel machine-learning jobs. The existing technology was taking too long to compute Zestimates, sometimes more than a day, which meant that customers weren’t getting updated information fast enough.

HeartFlow 是一家医疗技术公司，正在通过其非侵入性 HeartFlow FFRct 分析彻底改变心脏病的诊断和治疗。该技术利用深度学习创建个性化的心脏 3D 模型，使临床医生能够更好地评估阻塞对血流的影响并确定最佳治疗方案。然而，该公司面临着重大挑战。心血管疾病是世界上最主要的死亡原因，每年夺走超过 1700 万人的生命。最常见的类型是冠状动脉疾病 (CAD)，它会减少流向心脏的血液，导致胸痛、心脏病发作和死亡。临床医生需要知道是否存在阻塞、何处存在阻塞，以及它如何影响血流。这些信息对于为患者选择最佳治疗途径至关重要，例如医疗管理、支架置入或搭桥手术。然而，通常用于检测 CAD 的诊断性冠状动脉造影是侵入性的、昂贵的且存在潜在风险。超过一半接受测试的患者没有明显的阻塞，并且该过程可能会导致严重的并发症。

In 2016, the U.S. Department of Labor announced upcoming rule changes that would hold brokers and other investment advisers to a “fiduciary standard,” meaning they would be legally required to act in the best financial interest of their clients. This shift would restrict the types of investments that could be selected for certain retirement plans. Morningstar, Inc. recognized an opportunity to help employers find investments that comply with the fiduciary rule through an easy-to-use, online marketplace named Morningstar Plan Advantage. The marketplace would explain the regulations, offer searching and filtering of compliant investments, and ease enrollment into these plans. APIs connected to the application would allow investment providers to push data into the marketplace. Morningstar hoped to deliver an outstanding experience for employers and investment providers, and build revenue by increasing sales of plans for which they provide administrative services.

Movable Ink’s Intelligent Content Platform supports real-time personalization of email campaigns using up-to-date information from websites, social-media platforms, and APIs, as well as contextual data about device type, weather, recent user activity, and more. Additionally, it enables customers to analyze data about their users to make better marketing decisions. This process incorporates large and unpredictable amounts of data from a wide variety of sources, making the scale, elasticity, and connected nature of cloud services a logical fit. To meet these challenges, Movable Ink migrated its entire production environment to Amazon Web Services (AWS) in 2015, taking advantage of multiple regions and availability zones to provide redundancy, resilience, and scalability. In addition to the data and content used in personalized email messages, Movable Ink captures data on user behavior after users receive those messages, such as whether they opened the email, what items they clicked on, and what they browsed and purchased on websites as a result.

Veracode, a CA Technologies company, is on a mission to secure software applications so developers don’t release software that could be susceptible to breaches. As part of this mission, the company created Greenlight, a tool that helps developers discover and fix security-related defects while they are writing code. Because Greenlight is designed to find security flaws quickly, Veracode must ensure strong performance. “We need to deliver security vulnerability results in under a minute,” says Patrick Day, principal cloud engineer for Veracode. “If developers wait too long for the data, they’ll move on to a different product.” Veracode also needs to scale its solution to accommodate growth. “As we were building the application, we needed to plan for increases in code-scan volume,” Day says. As an application-development company, Veracode also strives to reduce the amount of time employees spend managing the IT environment. Day says, “We’re focused on developing and deploying products, so we don’t want to put our resources and energy into managing and provisioning.”

Amplframe, a photography community platform in Taiwan, was facing challenges in managing the increase in website traffic, with 18,000 visits over a period of seven months. The company needed a solution that could efficiently handle the sudden spikes in website traffic during events or holidays. Additionally, they were looking for ways to enhance the user experience by reducing webpage loading time and increasing the website engagement rate.

Firefly Learning, an online tool for teachers, students, and parents, was initially deployed by installing its software on Windows servers locally at each school. This setup presented numerous challenges, as supporting schools largely consisted of solving problems with their underlying infrastructure, such as dealing with backup issues and domain name system failures. As more schools adopted Firefly, the issues multiplied. The software was installed on hundreds of servers, and the task of supporting them all became overwhelming. Firefly needed a solution that would help join up the learning experience and allow for easier and more efficient support and management.

FuseFX, a visual effects company, was facing a challenge of lack of compute power, specifically, finding enough nodes for the compute-hungry process of rendering computer-generated imagery (CGI). The company was growing quickly in terms of size and the scope of its creative ambitions. One of the responsibilities was ensuring that the capacity of the FuseFX content-creation pipeline grows right along with the rest of the company. The company needed a solution that could provide unlimited computing power, the ability to expand rendering nodes quickly, affordably, and essentially infinitely.

Mirriad, a London-based company, delivers next-generation advertising solutions by using its computer vision technology to naturally place brands in premium video content across TV, online, and mobile channels. The challenge for Mirriad was achieving this intelligent insertion of ads at scale. The company was initially using physical data centers, which proved to be a bottleneck when it came to onboarding big businesses. In addition to fast access to compute capacity, another vital requirement for the company was the ability to use NVIDIA GPUs across multiple regions worldwide.

Springworks launched SPARK, a platform that lets car owners receive key data about their vehicles at the touch of a button, served straight from the cloud, direct to their smartphones. The platform also connects them with service providers that can sort any issues that might come up – from MOTs to tyre changes. However, each talking car generates about 10,000 data points per day. To handle 20 million cars, Springworks needed a system that could handle several billion data points in one go. They wanted limitless scale. In order to hit the market with a great new product, Springworks needed to be able to focus on innovation. When they started out, the release cycle as about 2 weeks for a new feature – but the team wanted to move faster. Finally, data security was a major concern. For a new market offer that was looking to partner with the big mobile networks, security couldn’t be an afterthought. It had to be built into the SPARK infrastructure from the start.

Edmunds, a company that helps consumers browse automobile dealer inventory, read vehicle reviews, and consume other automobile-related content, was planning a key update with better image quality and faster load times on the company's website and mobile apps. The company had a library of 50 million vehicle images that needed to be processed into several new aspect ratios and resolutions, resulting in more than half a billion new images. The company's existing image-handling solution, based on Cloudera MapReduce clusters, wasn't suitable for the job as it would have taken too long to develop and would have required the management of new clusters and incurred new monthly costs of at least $10,000.

GE Healthcare, a leading manufacturer and distributor of diagnostic imaging equipment, was seeking to improve patient outcomes by reducing workflow processing time through the sharing of medical image data across specialists and referring physicians. The company wanted to increase the value derived from device usage and data by enabling the leverage of cloud compute, storage, and access. The challenge was that up to 35 percent of patient cases were being misdiagnosed, partially due to a lack of access to images, data, and records. Additionally, better interoperability between systems could save healthcare ecosystems $30 billion per year, according to GE Healthcare.

Modernity Financial Technologies, Ltd. was facing the challenge of supporting a rapidly growing user base on its digital currency exchange and investment platforms, MaiCoin and MAX Exchange. The company needed a solution that could easily scale to accommodate a 563% average monthly member growth rate and an 894% average monthly cryptocurrency exchange rate. Additionally, the company wanted to decrease its daily operational time and reduce costs.

Matson, a leading U.S. shipping carrier in the Pacific Ocean, embarked on a journey to modernize its entire portfolio of enterprise applications and to upgrade and optimize every corner of its IT infrastructure. The shipping industry requires advanced IT capabilities to enable precise tracking of assets and customer shipments as they move around the world. Matson’s vessels, shipping terminals, container equipment, and truck shipments all require highly reliable technology to ensure that its transportation network operates at world-class levels. In addition, Matson’s customers count on cloud-based applications to provide real-time visibility and analytics in managing their own supply chains.

Vidsy, a London-based company that helps brands develop mobile-first video campaigns, was facing challenges with Docker Cloud. The company had moved all its applications into Docker containers running on Amazon EC2 instances and automated the administration of the containers using Docker Cloud. However, they regularly had to deal with Docker Cloud software bugs and dedicate precious engineering resources to fixing the issues. Furthermore, Docker Cloud’s cluster management feature was going end-of-life and Vidsy needed an alternative.

Commodity-crop farmers across the United States often depend on satellite images of their fields to get an updated view of the health of their crops. However, the resolution of these images is not high enough for farmers to get the most accurate picture of their fields. In fact, for many specialty-crop growers, satellite images are somewhere between useless and misleading. TerrAvion is changing that. The company uses airplanes and drones to obtain full-frame and thermal images from high-resolution cameras. TerrAvion gives farmers, retailers, agronomists, and ag distributors the best possible pictures through OverView, the company’s core subscription service. “Our pictures offer resolutions of 9 or 18 centimeters per pixel, which satellite can’t do,” says Stephen Smith, CTO of TerrAvion. Using such high-resolution images, farmers can more accurately view the health of a plant.

SolarNow, a for-profit social business, provides solar energy products and financing solutions in East Africa. The company faced challenges in identifying common device pain points for customers and optimizing device longevity. As SolarNow’s customer base grew, the company began identifying areas for business growth and improvement. They noted pain points for customers, such as a short battery lifespan or inefficient solar panel usage, that they felt they could proactively address and prevent these issues using Internet of Things (IoT) technology to build a connected device and monitoring solution. SolarNow needed to be able to enhance access to and use of device data to remotely monitor system performance and alert customers of inefficient device usage.

Zignal Labs, a company that helps its customers measure brand impact, mitigate reputation risks, and inform data-driven communications strategies, wanted to take existing sentiment classification techniques to the next level with a focus on reputation polarity. The company wanted to offer a solution that identifies the actual positive or negative impact of online content on a brand. Zignal Labs was all too familiar with the limitations of third-party sentiment-analysis solutions, having experimented with many of them itself. Some of these tools presented problems around scalability, and some weren't well suited to all the different media sources Zignal needed to track.

Stonehenge NYC, a private real estate group, was facing challenges with its outdated rental approval process and other tenant-related services. The company wanted to differentiate itself in the market by becoming technology-driven to drive efficiencies throughout its entire organization that result in a better customer experience. The team turned to Salesforce, a Customer Relationship Management (CRM) platform leader, to modernize the sales and leasing process. As the company continued to develop its Salesforce application and explore how new technologies, such as Internet of Things (IoT), would be key to its digital transformation journey, it chose to migrate its applications to Amazon Web Services (AWS).

Royal FloraHolland, a century-old company, recognized the importance of going digital to provide its growers and buyers with more opportunities. The company wanted to improve current processes and provide growers and sellers with new opportunities to reach buyers. The company recognized its need to reorganize in order to go digital and become more data-driven. Royal FloraHolland wanted to use other trading methodologies outside of the physical auction house to sell flowers. The company also wanted to improve the quality of the images that are presented at the auction and provide buyers with stock availability and alternative options tailored to their preferences.

TINE SA, a Norwegian cooperative owned by farmers, has been collaborating with Norway’s farmers for over 160 years to understand their challenges and help them drive efficiency, productivity, and high-quality dairy product development. As market demands increase, so does each farmer’s need to bring products to market more efficiently. TINE has a long history of developing decision-making tools for farmers and collecting data from different dairy products at the farm level. However, as TINE considered the future of dairy production at both the farm and national level, its data science team realized there would be changes to the breadth and depth of its data sources, types of data, and data analysis capabilities available to develop decision-making tools for farmers to use in production. TINE knew it would have to change its approach to data and technology by becoming more data driven as an organization to drive better predictability of milk production and other key data points related to a cow’s health and the quality of milk produced.

Companies experiencing rapid growth often lack the bandwidth to track each line of every contract, service agreement, or legal document before it’s executed. Even in the most carefully reviewed agreements, some information is forgotten as soon as the contract is signed. Once the business has matured and due diligence projects arise (for example, when a law changes or an acquisition takes place), companies must conduct detailed reviews of all signed contracts and identify specific terms within them. LinkSquares’ founders experienced the painful reality of reviewing existing legal contracts firsthand while their previous employer underwent an acquisition. The team identified existing software solutions helping companies efficiently address the pre-signature workflow: contract creation, terms negotiation, and internal workflow. However, the industry lacked a software solution to help companies mine for information in existing contracts.