AWS Startups Blog

Tag: Technical Use Cases

Shipper’s Digital Transformation Journey to Build Next Generation 4PL Supply Chain

In this blog post, Indonesian logistics startup Shipper shares their technology transformation journey and how they’ve grown and supported a couple hundred orders per day back in 2017 up to hundreds of thousands orders per day in recent years with the help of Amazon Web Services (AWS) managed services such as Amazon Elastic Kubernetes Service (Amazon EKS).

Carsome: Leveraging Automatic Car Plate Masking on Amazon SageMaker to Focus on Growth

Carsome is Southeast Asia’s largest integrated car ecommerce platform. With operations across Malaysia, Indonesia, Thailand, and Singapore, they aim to digitize the region’s used car industry by reshaping and elevating the car buying and selling experience. Here’s how they’re using Amazon SageMaker to free up resources to innovate.

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How HeyJobs Ingests Millions of Jobs with AWS Lambda

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%.

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HackerEarth Scales Up Continuous Integration for Future Needs with AWS

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.

latana improves brand tracking with statistics

Brand Tracking with Bayesian Statistics and AWS Batch

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.

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Creating Customized Business Applications with Clappia’s No Code Platform

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.

Achieve Better Price to Performance for TiDB on Amazon EKS with Graviton2 Processors

For startups, being able to save infrastructure cost while improving database performance and automating data layer operations can be crucial. Startups can then shift the cost savings for value innovations while at the same time improve their customer experience. While the value of running on Kubernetes is clear, some claim that this can be a costly affair for customers. In this blog, Pincap shares findings from a benchmark they conducted to compare price-performance ratio when running TiDB on Amazon EKS with AWS Graviton2 (Arm) and on the Intel Xeon Platinum 8000 series (x86).

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.

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.