AWS Startups Blog
Category: Artificial Intelligence
PulpoAR Uses Machine Learning to Build an Augmented Reality Shopping Experience for Beauty Products
PulpoAR looks to bring together the digital and physical worlds using augmented reality. The company has launched its platform with the ability to virtually try on makeup online, but plans to expand into other categories, like skincare, in the near future.
Paladin AI Looks to Improve Airline Pilot Training Using ML and AWS
Paladin AI is a company that uses machine learning to reinvent the pilot training process. Historically, aviation certifications relied heavily on subjective instructor scoring. The team at Paladin AI is looking to leverage data and ML algorithms to both make process easier and more accurate.
Accelerating Drug Development with Amazon Comprehend at Sumitovant
Sumitovant Biopharma seeks to discover the drugs of the future and rapidly get them to the patients who need them. Scientific research is key to their endeavor. To help us bring medicines to market faster, they need to pick out specific insights from the ever-growing body of literature on chemistry, biology, and disease. So they turned to Amazon Comprehend.
DISCO Transforms the Practice of Law Using AWS and Serverless Computing
Austin-based legal technology leader DISCO is on a mission to reinvent the practice of law through software by making lawyers more efficient in everything they do. Founded in 2013, it has revolutionized the way law firms and corporate legal departments operate, using technology and cutting-edge AI to analyze data quickly and free up resources for tasks that require legal judgment. DISCO provides a key competitive advantage in an industry where speed and accuracy are critical.
Olive Builds the Internet of Healthcare and an AI Workforce on AWS
Today, the healthcare industry is flooded with software. Any given hospital has an EMR, billing software, different portals for every insurance partner, and individual medical tools each with their own interfaces, just to name a few. None of these systems work together, and the downstream effects dehumanizes the care experience. Olive is designed to connect these disparate parts, shining a new light on old processes, connecting providers delivering care and payers reimbursing that care to ultimately drive a better patient experience.
Causality Link Uses Amazon Translate to Bring in Global Perspectives
As an investor, Eric Jensen, co-founder and CTO of Causality Link, was frustrated with how difficult and time consuming it was to project trends in financial markets. Too often, he found there was either no information available or only regurgitated sources, and he decided to change how investors consume information to make decisions. Eric started Causality Link to empower investor decisions with natural language processing (NLP) and provide information from around the globe in a consolidated and interactive platform.
Flo: Advancing Women’s Health with ML and Amazon SageMaker
The body is often a mystery, and it’s nice when an external source is able to provide expert, evidence-based information about it. Flo App, a holistic health and wellbeing platform that helps women understand their bodies and minds, was built to do just that. Founded in 2015, Flo supports women as they make better informed decisions about their reproductive, physical, and mental health.
How Startups Deploy Pretrained Models on Amazon SageMaker
For most machine learning startups, the most valuable resource is time. They want to focus on developing the unique aspects of their business, not managing the dynamic compute infrastructure needed to run their applications. Productionizing machine leaning should be easier, and that’s where AWS comes in. In this blog post and corresponding GitHub repo, you will learn how to bring a pre-trained model to Amazon SageMaker to have production-ready model serving in under 15 minutes.
Understanding the New World of Office Space with Basking
Overnight, the COVID-19 pandemic reshaped how and where Americans work. By June, according to a survey from Stanford researchers, 42% of the U.S. labor force was working from home full time, with millions more not working at all. For employers, that shift has led to new challenges as they navigate an unprecedented economy. One big question: what to do with all the empty offices?
Emedgene’s Migration to AWS for its AI-based Genomics Insights Platform
Founded in 2015, Emedgene has built an AI-based platform to automatically surface insights from genomics data. Previously, this data would need to be analyzed by genomics experts, of which there are only a few thousand around the world. Emedgene applies machine learning algorithms to generate these insights on the fly, essentially teaching computers how to be genetic researchers.