The challenge
Aiberry needed to build a SaaS product to provide quantitative analysis, mental health insights, and risk scores to health care providers in real time during short interviews from captured media. As a scaling startup, Aiberry knew they needed to build their platform on DevOps best practices in order to stay competitive, but didn't have the resources necessary to build a DevOps-centric platform.
The solution
Sela’s solution relied heavily on DevOps services on AWS. Media streams were converted to raw transcripts, with ML inference used to predict patient suicidality using:
- Lambda + Step functions
- ECS
- SQS
- DynamoDB
- Sagemaker
- AWS Comprehend
A simple user interface was built for clinicians and patients and deployed to a secure, multi-account AWS environment using containers running on ECS. AWS SSO provided secure roles and permissions for users. Infrastructure builds across tenants and regions were automated with AWS CDK, Gitlab, and CodePipeline.
The results
Aiberry is now able to quickly adapt their system to changing requirements, new research, and new technology. Documentation and training on the simplified end-user application make it easier to use and understand. This translated into greater subscriber growth via faster onboarding and a better user experience with fewer support issues and performance problems.
The DevOps-centric system performs faster and costs less per user to operate. The product is easier to innovate and deploy.
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