AWS Startups Blog

Cumbersome, disparate data sources in highly regulated environments have historically obstructed longitudinal patient views in clinical research. To help clients generate maximum evidence from trials, Precision Digital Health (PDH) developed a cloud-based platform capable of integrating and harmonizing disparate data assets in the R&D and life sciences industry.

Artificial intelligence may be the future, but 90% of AI models developed today don’t make it into production. DarwinAI has set out to solve that problem by enabling organizations to understand and optimize models, making it easier to build what matters.

HeyJobs aims to be the leading platform for those looking for the right job to live a fulfilling life. Serving millions of job seekers means that they need to ingest hundreds of thousands to future millions of job-offering details, multiple times a day, every day. Gokay Kucuk, an engineering manager on the inventories and integrations teams, shares their learnings about the AWS services they utilized for their serverless transformation. At the end of this transformation, the job ingestion capacity of HeyJobs grew from few hundred thousand to few millions per day while reducing their costs by ~30%.

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.

One of the goals of every fast-paced organization is to have a Continuous Integration (CI) pipeline that ensures every check-in is best verified before it can be pushed to production. HackerEarth wanted to achieve a CI model that has enough safety nets for every check-in that goes into each Pull Request (PR), as well as make the process scalable and cost effective. These safety nets in the pipeline provide constructive feedback for the PR, and the necessary steps are then taken to mitigate the gaps. For integration tests in this pipeline, HackerEarth used AWS CodeBuild along with Amazon S3 and Amazon ECR.

FutureFit AI’s platform is designed to help guide individuals through the process of planning their careers. It starts with first figuring out where they are, then gaining an understanding of where they want to go and helping them map a course between points A and B.

Brand tracking startup Latana’s Senior Data Scientist Corrie Bartelheimer outlines how mathematical models and probability theory, specifically Bayesian methods, address some of the big problems in brand marketing and how AWS Batch, together with Metaflow, solves many of the technical issues that used to be major obstacles to using Bayesian methods at scale.

Clappia is a no code platform where creating customized business applications is as easy as working with Excel sheets. Apps built on Clappia range from elementary to very complex, involving master data, automation workflows, and integrations with external systems. Its co-founders, Ashutosh Kumar and Sarthak Jain, walk us through how they achieved success.

The AWS SaaS Factory team invited Founder and Chief Product Officer of Dremio, Tomer Shiran, to discuss Dremio’s journey to software-as-a-service and to share key learnings for businesses building SaaS and platform-as-a-service (PaaS) offerings on AWS.

Real estate software startup Qbiq system delivers an artificial intelligence (AI)-driven space planning design engine that generates large volumes of customized floor plans, compares alternatives, and optimizes the results. They relied heavily on AWS Lambda image containers to achieve scale. Here’s how they did it.