Category: Case Study

In this post, we explore Clearwater Analytics’ foray into generative AI, how they’ve architected their solution with Amazon SageMaker, and dive deep into how Clearwater Analytics is using LLMs to take advantage of more than 18 years of experience within the investment management domain while optimizing model cost and performance.

In the dynamic world of streaming on Amazon Music, every search for a song, podcast, or playlist holds a story, a mood, or a flood of emotions waiting to be unveiled. These searches serve as a gateway to new discoveries, cherished experiences, and lasting memories. The search bar is not just about finding a song; […]

MDaudit provides a cloud-based billing compliance and revenue integrity software as a service (SaaS) platform to more than 70,000 healthcare providers and 1,500 healthcare facilities, ensuring healthcare customers maintain regulatory compliance and retain revenue. Working with the top 60+ US healthcare networks, MDaudit needs to be able to scale its artificial intelligence (AI) capabilities to […]

In this post, we discuss how United Airlines, in collaboration with the Amazon Machine Learning Solutions Lab, build an active learning framework on AWS to automate the processing of passenger documents. “In order to deliver the best flying experience for our passengers and make our internal business process as efficient as possible, we have developed […]

This is a guest post co-written by Julian Blau, Data Scientist at xarvio Digital Farming Solutions; BASF Digital Farming GmbH, and Antonio Rodriguez, AI/ML Specialist Solutions Architect at AWS xarvio Digital Farming Solutions is a brand from BASF Digital Farming GmbH, which is part of BASF Agricultural Solutions division. xarvio Digital Farming Solutions offers precision […]

Learn how Yara is using Amazon SageMaker features, including the model registry, Amazon SageMaker Model Monitor, and Amazon SageMaker Pipelines to streamline the machine learning (ML) lifecycle by automating and standardizing MLOps practices. We provide an overview of the setup, showcasing the process of building, training, deploying, and monitoring ML models for plants around the globe.

LiDAR is a key enabling technology in growing autonomous markets, such as robotics, industrial, infrastructure, and automotive. LiDAR delivers precise 3D data about its environment in real time to provide “vision” for autonomous solutions. For autonomous vehicles (AVs), nearly every carmaker uses LiDAR to augment camera and radar systems for a comprehensive perception stack capable […]

This blog post is co-authored by Guillermo Ribeiro, Sr. Data Scientist at Cepsa. Machine learning (ML) has rapidly evolved from being a fashionable trend emerging from academic environments and innovation departments to becoming a key means to deliver value across businesses in every industry. This transition from experiments in laboratories to solving real-world problems in […]

This blog post is co-written with Nick Vargas and Anna Schreiber from Accenture. Scheduling customer appointments is often a manual and labor-intensive process. You can utilize advances in self-service technology to automate appointment scheduling. In this blog post, we show you how to build a self-service appointment scheduling solution built with Amazon Lex and Amazon […]

This post is co-written with Sowmya Manusani, Sr. Staff Machine Learning Engineer at Zendesk Zendesk is a SaaS company that builds support, sales, and customer engagement software for everyone, with simplicity as the foundation. It thrives on making over 170,000 companies worldwide serve their hundreds of millions of customers efficiently. The Machine Learning team at […]