Editor’s Note
This article highlights how a fintech firm leverages Google Cloud’s Vertex AI and Kubernetes Engine to automate its KYB compliance process. The AI-driven system uses natural language processing to streamline customer verification, reportedly boosting productivity 30-fold and significantly cutting onboarding times.
A fintech group specializing in foreign exchange and cross-border payment solutions uses Vertex AI and Google Kubernetes Engine to power its AI-driven Know Your Business (KYB) compliance solution. The natural language processing-based system automates compliance tasks and improves productivity by 30 times, reducing onboarding times and eliminating manual bottlenecks in customer verification.
A public company with 10,000 employees producing sustainable packaging, hygiene, and recovery solutions migrated its business-critical SAP environment to Google Cloud and uses BigQuery as a central data repository for employees across the company to run queries predicting financials, monitoring customer demand, and balancing manufacturing schedules.
A company uses BigQuery and Vertex AI to predict demand for specialized sealing materials used in aircraft assembly. The system reduced monthly material waste from several million yen to eventually achieving zero waste, while enabling the team to run multiple prediction scenarios and refine accuracy based on factors like daily temperature and worker experience levels.
A Swedish startup has created an app to gamify recycling, offering rewards to users across the Nordics and UK; they’ve integrated generative AI into the service so users can more easily identify and input recyclable goods into the app.
A startup researching zero-waste, bio-based alternatives to fossil-fuel-made products like plastics is creating a gen AI tool that enables entrepreneurs to develop novel compostable materials with broad applications; AI enables faster research and information gathering to speed up the development process.
A global pioneer of ethical cosmetics uses Vertex AI and Cloud Storage to power Lush Lens, an AI-powered image recognition system that identifies packaging-free products at checkout. The system reduced queue times during peak Christmas shopping from out-the-door to just 3 minutes, while saving 440,000 liters of water previously needed for product demonstrations.
A company uses Vertex AI Forecast to predict product demand and optimize inventory levels in its distribution centers. This AI-powered forecasting has resulted in a 43% improvement in forecasting accuracy, leading to reduced food waste and improved sustainability.
One of Croatia’s leading food and retail companies created an AI inventory helper that provides grocery store managers with fresh insights to help them place more accurate orders for perishables like fruits and vegetables, reducing food waste while boosting profits.
A UK company developing AI-powered waste sorting robots called ALPHA built its Robots-as-a-Service platform on Google Cloud using Compute Engine, Cloud Data Fusion, and Cloud Storage to manage over 49 terabytes of hyperspectral imaging data. The company reduced simulation runtime dramatically and projects a 10% improvement in material recovery efficiency with potential future gains up to 50%.
A year and a half ago, during Google Cloud Next 24, we published this list for the first time. It numbered 101 entries. It felt like a lot at the time, and served as a showcase of how much momentum both Google and the industry were seeing around generative AI adoption. In the brief period then of gen AI being widely available, organizations of all sizes had begun experimenting with it and putting it into production across their work and across the world, doing so at
What a difference these past months have made. Our list has now grown by 10X. And still, that’s just scratching the surface of what’s becoming possible with AI across the enterprise, or what might be coming in the next year and a half.