AIP-C01 · Question #13
An elevator service company has developed an AI assistant application by using Amazon Bedrock. The application generates elevator maintenance recommendations to support the company's elevator…
The correct answer is B. Create an AWS Step Functions workflow that has a human approval step that uses the. AWS Step Functions provides native support for human-in-the-loop workflows, making it the best fit for regulatory oversight requirements. The waitForTaskToken integration pattern is explicitly designed to pause a workflow until an external actor--such as a human…
Question
An elevator service company has developed an AI assistant application by using Amazon Bedrock. The application generates elevator maintenance recommendations to support the company's elevator technicians. The company uses Amazon Kinesis Data Streams to collect the elevator sensor data. New regulatory rules require that a human technician must review all AI-generated recommendations. The company needs to establish human oversight workflows to review and approve AI recommendations. The company must store all human technician review decisions for audit purposes. Which solution will meet these requirements?
Options
- ACreate a custom approval workflow by using AWS Lambda functions and Amazon SQS queues
- BCreate an AWS Step Functions workflow that has a human approval step that uses the
- CCreate an AWS Glue workflow that has a human approval step. After the human technician
- DConfigure Amazon EventBridge rules with custom event patterns to route AI recommendations to
How the community answered
(49 responses)- A16% (8)
- B73% (36)
- C4% (2)
- D6% (3)
Explanation
AWS Step Functions provides native support for human-in-the-loop workflows, making it the best fit for regulatory oversight requirements. The waitForTaskToken integration pattern is explicitly designed to pause a workflow until an external actor--such as a human reviewer--completes a In this architecture, AI-generated recommendations are sent to a human technician for review. The workflow pauses execution using a task token. Once the technician approves or rejects the recommendation, an AWS Lambda function calls SendTaskSuccess or SendTaskFailure, allowing the workflow to continue deterministically. This approach ensures full auditability, as Step Functions records every state transition, timestamp, and execution path. Storing review outcomes in Amazon DynamoDB provides durable, queryable audit records required for regulatory compliance.
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