Question

A retail company is building a returns-processing assistant. The workflow requires: (1) validating an order number against a fulfillment API, (2) checking return eligibility based on a business-rules engine, and (3) generating a refund confirmation. The order in which these steps run can vary depending on customer input, and the LLM must decide which tool to invoke next based on intermediate results. The team wants to minimize the amount of custom orchestration code they maintain while still allowing the model to reason dynamically about which action to take. Which implementation approach best fits these requirements?

Accepted Answer

Build a Bedrock Agent with action groups mapped to Lambda functions for the fulfillment API and rules engine, and let the agent's orchestration handle tool selection dynamically.

Answer

Implement a Step Functions Standard workflow with explicit state transitions for each of the three steps and a Choice state to branch on results.

Answer

Use a single Lambda function that hardcodes the three API calls in sequence and passes intermediate results into successive InvokeModel calls.

Answer

Deploy an API Gateway endpoint that invokes InvokeModel once with a large system prompt describing all three steps and expects the model to call all APIs itself.