AWS Startups Blog
Category: AWS Batch
FloodMapp Leverages AWS for Real-Time Inundation Flood Mapping to Save Lives and Assets
FloodMapp is a world-first flood modelling solution, purpose-built for flood forecasting and early warning. Aimed at improving safety and preventing damage, FloodMapp provides highly accurate, real-time, property-specific, and dynamic flood inundation and depth insights for businesses exposed to flooding. It is 10,000 faster and 200 higher resolution than traditional models in an emergency response setting. Here’s how it works.
Reverie Labs: Scaling Drug Development with Containerized Machine Learning
Reverie Labs uses computation to drive the development of therapeutics for cancer. To do this, they’ve built substantial cloud-based infrastructure to train machine learning models, deploy models to production, and build and ship internal-facing applications for our chemistry teams.
Datavant Uses Batch to De-Identify Health Data
Datavant enables health companies to share sensitive health data securely. An important part of this process is de-identifying records so that they can be used in research or analytics contexts where identifying information is unneeded or required by law to be removed. Datavant supports both on-premise and cloud workflows to de-identify data. In this post, we share a simple approach to turn our native on-premise application into an AWS-hosted cloud service over the course of a single sprint cycle.
Scaling High-Throughput Genomics Workflows on AWS
Guest post by Tomaz Berisa, Cofounder and CTO at Gencove We have been working hard to scale low-pass sequencing at Gencove and ran into a few computational scalability constraints. This is an overview of how we got around them and the resulting architecture, complete with infrastructure templates and code. Sequencing the first human genome in […]