How Boomi Scribe streamlines documentation using AWS

Boomi Scribe addresses the challenge of maintaining accurate documentation for complex enterprise workflows, which is often manual, time-consuming, and error-prone. By automating this process, Boomi Scribe helps reduce technical debt and enhances developer productivity.

The solution leverages AWS AI/ML services, including Amazon Bedrock and Amazon SageMaker, to parse integration DAGs stored as XML files, extract relevant features, and generate comprehensive documentation. The process involves transforming DAGs into a structured dot notation format, which is then processed by large language models like Claude Haiku 4.5 to produce detailed descriptions, process overviews, and metadata.

The architecture is built for scalability and reliability, utilizing Amazon S3 for storage, DynamoDB for backend data management, and AWS Lambda for orchestration. The system also compares different versions of DAGs to highlight changes, providing developers with insights into process modifications.

This automated documentation process not only saves time—reducing manual effort by up to 85% in some cases—but also ensures consistency and accuracy across process versions. The generated documentation is accessible within the Boomi platform, supporting version control, easy retrieval, and integration into developer workflows.

Overall, Boomi Scribe exemplifies how cloud-based AI services can streamline enterprise process documentation, improve compliance, and support large-scale automation efforts.