GCP – Cool stuff customers built, May edition: Visual scouts, racing agents, agile ads & more

AI and cloud technology are reshaping every corner of every industry around the world. Without our customers, there would be no Google Cloud, as they are the ones building the future on our platform. In this monthly round-up, we dive into some of the exciting projects redefining businesses, shaping industries, and creating new categories. 

For our inaugural edition, we explore Lowe’s new Visual Scout product recommendation engine powered by Vertex AI Vector Search; a responsive “Driver Agent” platform created by Formula E to bring more equity to the track; Ester AI, a conversational tool from wealth.com that can help financial planners review wills and trusts; a new operational dashboard that’s improving service for African super app Yassir; and AI-powered knowledge base health insurer SIGNAL IDUNA is using to enhance customer experience; how AlloyDB helped autonomous driving company Nuro manage millions of real-time image queries more efficiently and cost effectively; and Mars Wrigley can now measure and update ads more agilely with Cortex Framework.

Be sure to check back in June to see how more industry leaders and exciting startups are putting Google Cloud technologies to use. And if you haven’t already, please peruse our list of 601 real-world gen AI use cases from our customers.

Lowes’ Visual Scout sees sales boost

Who: One of the world’s leading hardware store chains, Lowe’s faced a common ecommerce challenge: Many of its customers come to the site or mobile app without a clear idea of what they want but believe that they will recognize the right product when they see it.

What they did: Using Vertex AI Vector Search to help build connections across products, Lowe’s created Visual Scout. It offers an interactive experience for customers to discover a variety of styles within a product group, starting with a panel of 10 items. Customers then indicate their preferences by “liking” or “disliking” items in the display, and then Visual Scout dynamically updates the panel with items that reflect customer preferences.

Why it matters: As the service updates in real time, Visual Scout provides an engaging and gamified shopping experience that encourages customer engagement and, ultimately, conversion.

Learn from us: “Both [Vector Search and Feature Store] help Visual Scout process a high volume of requests while maintaining low-latency responses. The 99th percentile response times of approximately 180 milliseconds align with our performance expectations, and ensures a smooth and responsive user experience.” – Zaid Alibadi, Senior Manager for Data Science, Lowe’s & Olga Stolpovskaia, Senior Data Scientist, Lowe’s

Formula E’s Driver Agent boosts the next generation of racers

Who: Formula E is a new racing league whose radical eclectic-powered cars are meant to pave the way for the road cars of tomorrow, with the series acting as a competitive platform to test and develop the latest in electric technology.

What they did: Formula E launched the “Driver Agent,” an AI tool powered by Google’s Vertex AI platform and Gemini models, aimed at expanding access to race insights for more teams. The Driver Agent is designed to analyze extensive multimodal data generated during racing and provide actionable insights to drivers, helping democratize access to data-led analysis and coaching.

Why it matters: Google Cloud is actively supporting More than Equal’s mission of identifying and developing elite female racing talent, and the Driver Agent helps fulfill this shared mission with Formula E. Race analysis in the Driver Agent is aimed at helping optimize braking and acceleration, generate more downforce, avoid crashes — and, chiefly, improve lap times, which testing has shown to be the case.

Learn from us: “Formula E has always been a platform for innovation… By developing and offering these cutting-edge tools, we are helping to create a future where racing talent is determined by skill, not resources, enabling a more diverse pool of drivers and especially women, rise to the very top of our sport.” – Beth Paretta, VP for Sporting, Formula E

Wealth.com reshapes legacy planning

Who: Wealth.com bills itself as “estate planning reimagined,” where a combination of best-in-class technology, AI, and human expertise are combined to elevate the wealth management industry to new levels of service and efficiency.

What they did: It could take even an experienced financial planner hours if not days to understand complex estate planning documents, like trusts, that can run to hundreds of pages. Wealth.com built its Ester AI to solve this by quickly absorbing the information in the documents and automating the most relative and low-value tasks, freeing advisors to focus on valuable work like building better plans and providing better customer relations.

Why it matters: Traditional machine learning models simply can’t handle the scale or complexity of estate planning documents. The team at wealth.com found that Gemini’s industry-leading long context window allowed Ester to achieve a level of understanding previously unattainable. In fact, Ester has identified critical information even wealth.com’s experienced legal team overlooked — an impressive example of how AI can augment human expertise.

Learn from us: “Building Ester itself was no easy task. The complexity of estate planning documents required a careful balance of automation and human oversight. The latter, in the form of our legal experts, lays a critical role in annotating datasets and validating outputs.” – Seungwoo Son, VP of Applied AI, Wealth.com

African super app Yassir delivers on data

Who: Yassir is a super app, supporting the daily lives of users in more than 45 cities across Algeria, Morocco, Tunisia, South Africa, and Senegal who rely on our ride-hailing, last-mile delivery, and financial services solutions.

What they did: The company had two separate data systems, one using Databricks for deploying and training machine learning models and another through Google Cloud and BigQuery for storing and analyzing data. This setup led to several issues, such as formatting incompatibilities and disconnected data. Yassir consolidated its data infrastructure with Google Cloud to bring all of these functions into one place, providing better access to data and more scalability, as well as new opportunities to analyze, review, and improve performance.

Why it matters: Operational dashboards give sales and marketing teams the insights they need to better target and reach merchants and consumers. They also include insights into our staffing processes, helping us to gradually reduce delivery times, complete more rides faster, and improve how we support specific markets. We also have product-level detection and monitoring that help us provide real-time dynamic pricing and identify fraudulent trips and orders.

Learn from us: “With our data unified in BigQuery and connected to our machine learning models, we can better support everything from customer growth and retention to marketplace optimization by providing insights into product usage, customer data, and more.” – Hamdi Amroun, Head of AI, Yassir & Maniganda Perumal, Data Platform Lead, Yassir

SIGNAL IDUNA supercharges customer service

Who: SIGNAL IDUNA is a leading German insurance provider that is particularly active in the private and supplementary insurance market, as well as covering home and auto.

What they did: SIGNAL IDUNA, in collaboration with Google Cloud, BCG and Deloitte, has developed an AI knowledge assistant that empowers service agents to quickly and accurately resolve complex customer inquiries. 

Why it matters: This innovative solution uses Google Cloud AI, including Google’s multimodal Gemini models, to help agents find relevant documents and provide comprehensive answers 30% faster — ultimately, enhancing customer satisfaction. And with support from the AI knowledge assistant, SIGNAL IDUNA’s case closure rate increased by approximately 24 percentage points, rising from 73% to almost 98%.

Learn from us: “We’ve pioneered to unlock the power of human-AI collaboration: To redefine process efficiency by bringing together technology and subject matter experts to deliver exceptional customer experiences.” – Johannes Rath, board member for Customer, Service, and Transformation at SIGNAL IDUNA

NURO drives AI-powered insights with AlloyDB

Who: Nuro’s motto is “Autonomy for all. All roads, all rides.” The Silicon Valley-based startup is building an AI-powered Nuro Driver mobility platform, which is designed to be open to automotive and mobility companies.

What they did: Nuro needed a data platform that could handle complex data processes and support continuous AI model improvement. By migrating to AlloyDB for PostgreSQL, the company gained the scalability, high performance, and advanced query capabilities needed to power AI-driven insights that could manage real-world situations across millions of data points, while also reducing operating costs.

Why it matters: Since migrating to AlloyDB AI, Nuro has seen a substantial reduction in the operational costs of storing and searching embeddings. With ScaNN indexing, searches now yield more than 20,000 high-precision results in seconds, outperforming alternative indexing methods like IVF and HNSW in both quality and scalability.

Learn from us: “Our partnership with Google Cloud has also been invaluable. We have continuous access to innovations from the Google Cloud team, and we can easily meet any database requirement by leveraging their extensive suite of products. This support has accelerated our development, enabling us to focus on what matters most — advancing autonomous technology.” – Fei Meng, Head of Data Platform, Nuro

Mars Wrigley’s agile media experiments

Who: For more than a century, Mars Wrigley has made some of the world’s most popular candies and other consumer products. One way it maintains this status is through technology-driven advertising and marketing

What they did: By combining data in BigQuery and using built-in data science tools like BQML, Mars Wrigley can now better understand how specific audience targeting strategies in its media investments are driving incremental sales lift across key customer groups. Mars Wrigley then used Cortex Framework to gain instant insights through predefined and customizable analytics content as well as seamless integration with major media platforms like Google Ads, YouTube, TikTok, Meta, and more.

Why it matters: By embracing Cortex Framework, Mars Wrigley is not only gaining a clearer understanding of media impact on sales but also paving the way for a more data-driven and agile approach to marketing in the consumer packaged goods industry. This includes the ability to execute agile hypothesis testing, scalability to match media investments, and greater versatility to test media formats, content variations, shopper media, and more.

Learn from us: “Before, we were struggling to get an accurate in-flight view of our audiences’ performance. With Google Cloud Cortex Framework, we realized that the answer was within our internal data. We partnered with EPAM Systems to harness the synergy of our internal data sources, enabling us to run timely experimentation based on actual sales lift.” – Lía Inoa Pimentel, Senior Global Manager, Brand Experience & Media Measurement, Mars Wrigley