Serverless AI integration
Clinical Intake Assistant
An AWS Lambda and Amazon Bedrock backend that converts intake information into structured JSON.
- Role
- Backend and AI Engineering
- Project type
- Serverless AI integration
- AWS Lambda
- Amazon Bedrock
- Structured JSON
Overview
Problem and context
Intake information can arrive in a form that is difficult for downstream software to process consistently. The system needed to transform that information into a defined structure without implying medical diagnosis.
What was built
The implementation uses AWS Lambda to invoke Amazon Bedrock and return structured intake JSON through a backend boundary.
My Contribution
- Implemented the serverless processing path with AWS Lambda and Amazon Bedrock.
- Defined the boundary between intake input, model processing, and structured JSON output.
- Kept the system positioned as intake structuring rather than diagnosis or clinical decision-making.
Engineering
Serverless execution boundary
AWS Lambda contains the backend processing step, keeping model invocation out of the client interface and providing a clear API-side execution boundary.
Bedrock integration
Amazon Bedrock supplies the model capability used to interpret intake information within the Lambda workflow.
Structured output contract
The output is structured intake JSON so downstream software receives data in a defined machine-readable form rather than free-form generated text.
Outcome
- Converted intake information into structured JSON through a serverless backend path.
- Separated model integration from the consuming interface and downstream systems.
- Kept the implementation scope limited to structuring intake information, not medical diagnosis.
Tech Stack
- AWS Lambda
- Amazon Bedrock
- Structured JSON