Author: Mikey Tom

Didimo, which means “twin” in Greek, has built a platform for creating realistic 3D digital versions of people, based on simple photos or scans. That capability has potential applications in a host of industries, from AR/VR and video games to retail, fashion, and communications—really anywhere people want to have authentic, engaging, immersive experiences.

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.

Founded in 2016, Kavak is the digital platform that’s making it easier than ever to buy and sell cars. The Mexico City-based founded startup recently achieved “unicorn” status after reaching a $1.15 billion valuation, the first tech company in the country to do so. As Kavak expands its operations to Argentina and sets sights on Brazil, we sit down with Vice President of Data Science, Anders Christiansen, to chat about how machine learning and AWS serverless services helped build the engine behind the company’s ever-improving workflow.

There’s been plenty of attention paid by the media to the problems of facial recognition software in recent years. Invasion of privacy, for one, and high potential for misuse, for another. AIH Tech, a Toronto-based computer vision company, has set out to solve the problem that most other facial recognition technologies have faced in their bedrock: racial bias.

The fight against breast cancer has made progress over the past two decades thanks to advances in treatment and screening. But while mortality rates from the disease have fallen for women over 50, they remain frustratingly steady for younger women. Onkolyze, a startup based in Singapore, is hoping to help solve just that problem by applying high-powered AWS GPUs and ML, making early detection much easier.

Aha! is a leading roadmap software provider, helping more than 400,000 users build products and counting north of 5,000 companies as customers. Founded in 2013 with an entirely distributed team, the company puts customer needs at the heart of its business model. Read how the company was able to drive results by migration to Amazon Athena from BigQuery.

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.

Audioburst is on a mission to build the world’s largest talk audio repository, enabling anyone to easily search for and share content. Initially, the company launched on Azure, but has since fully migrated to AWS for managing its Kubernetes-based system. Since moving, Audioburst has been able to take advantage of multiple other services within the AWS ecosystem, such as Amazon Transcribe. Watch the above video to hear from CTO Gal Klein on what went into the decision to migrate and how it’s been since the move.

Finding the right data, both internally and externally, for your ML can be a huge pain, though. It’s often dirty, hidden behind paywalls, or just not enough to give a full view of a situation. This is where Explorium comes in.

Headquartered in New York, Rally has built a platform that turns collectible items into investable securities, enabling anyone to take part in the potential financial upside of owning high-value assets. From Aston Martins to rare Hermès Birkin bags, Rally users can browse the various categories, select which items to learn more about, and purchase shares in whatever catches their eye, all from the company’s mobile app.