Using AWS Lambda to save time & money
Learn how PGS Software helped a Norwegian start-up to create a mobile application whose technology allows users to decode their health symptoms and track what affects their condition.
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PGS Software is an APN Consulting Partner certified in designing and implementing SaaS solutions and as such was able to work with Sybod to derive the greatest possible benefits of using Amazon Web Services.
- AWS Lambda delivered cost savings and scalability
- Thanks to AWS, less time was spent on dealing with server-related issues
- The Apache Cassandra database guaranteed Big Data readiness
- Resources were spent on business needs, and not on maintaining a server
- The AWS Cloud made the application agile and future-proof
Sheyeen Liew, CEO of Sybod, wanted to improve people’s quality of life by using the latest in machine learning technology to automate the analysis of their chronic health conditions.
All she needed was to find a skilled software development team capable of creating a Big Data-ready, robust, and scalable application that would be able to process and store large amounts of data points. That is when she turned to PGS Software.
Using AWS Lambda has definitely saved us a lot of hassle. If we were to host the app on our own server, a lot more time and money would have been spent on dealing with server-related issues… Whenever we faced a challenge, the PGS Software team would come and say that we have a problem. However, they would also say – here are three different solutions to that problem and here is the cost-benefit of each possible solution. Thanks to their technical expertise, we were able to make good business decisions at a higher level rather than having to try to dig into all of the technical details.
— Sheyeen Liew, CEO, Sybod
AWS Lambda, AWS EC2
iOS, Swift, Apple HealthKit, Apache Cassandra Java, Node.js, Dynamo DB, Git
About the Client
Sybod is a start-up from Norway run by Sheyeen Liew. The Sybod application aims to improve people’s quality of life by using the latest in machine learning technology to automate the analysis of users’ chronic health conditions.
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