AWS Startups Blog

Tag: Technical Use Cases

How AMPLYFI Manages Variable Traffic Machine Learning Workloads on AWS Lambda

Founded in 2015, AMPLYFI has developed an insight automation platform that helps organizations to make better decisions and change with conviction. AMPLYFI specializes in developing artificial intelligence driven solutions that unlock and analyze the vast amounts of unstructured data on the internet, internal company datasets, and industry databases, allowing customers to generate key decision-driving insights.

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Sparta Science: Predicting Musculoskeletal Injury Risk with Force Plate Machine Learning™ on AWS

Sparta Science delivers a movement health solution to organizations who want to protect their most valuable resource – people. Elite sports teams, military units, performance and rehabilitation businesses, occupational health providers, and employers use Sparta Science’s Movement Health Platform (SMHP) to assess injury risk and performance, and to guide improvements in musculoskeletal health. Here’s how they’re leveraging AWS to do it.

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MatHem.se Scales Grocery Delivery App with Amazon EventBridge

In March 2020, MatHem.se, Sweden’s leading independent pure-play online grocery retailer, saw a huge surge in customer demand almost overnight. The number of concurrent users trying to place a grocery order increased by 800% day-over-day. Here’s how they used a serverless architecture and Amazon EventBridge to handle the strain.

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The Journey to Secure Part 2 – FYI

We recently shared the story of Tic:Toc, a digital home loan scale-up based in Adelaide, Australia, and the steps they took to set their initial foundations. Once your foundations are in place, having a process in place for assessing your architecture is important in building on top of that foundation. To learn more about how customers are evolving their security posture, we sat down with Alan McLeod, the CTO at FYI.

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Digital Insight Scales Up or Down Rapidly for Their Bursty Inference Workloads

Digital insight has built a platform for automated due diligence research. However, the technical challenge that sits underneath is enormous. The amount of data that must be collected and analyzed to create each report is vast (much greater than a human would ever be able to explore alone), and the compute resources required to do this must be provisioned in seconds in order to meet their five-minute goal. Toby Miller, a Technical Architect at the startup, walks through how they addressed this challenge.

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