This post is co-written with Swagata Ashwani, Senior Data Scientist at Boomi.
Boomi is an enterprise-level software as a service (SaaS) independent software vendor (ISV) that creates developer enablement tooling for software engineers. These tools integrate via API into Boomi’s core service offering.
In this post, we discuss how Boomi used the bring-your-own-container (BYOC) approach to develop a new AI/ML enabled solution for their customers to tackle the “blank canvas” problem. Boomi’s machine learning (ML)-powered solution facilitates the rapid development of integrations on their platform, and enables faster time to market for their customers. Boomi funded this solution using the AWS PE ML FastStart program, a customer enablement program meant to take ML-enabled solutions from idea to production in a matter of weeks. Boomi built this solution using Amazon SageMaker Studio, an end-to-end browser-based IDE for AI/ML workloads, and Amazon Elastic Container Registry (Amazon ECR).
The blank canvas problem describes

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