How to Build a Serverless AI Agent with Amazon Bedrock and Lambda

Last month I needed an internal tool that could answer HR questions — leave balances, policy lookups, team schedules. The obvious approach was a chatbot, but a plain LLM just hallucinates answers it doesn't have. It needs access to actual data. Amazon Bedrock Agents solve this by letting an LLM call backend functions through what AWS calls "action groups." The LLM reads function descriptions, decides which one matches the user's question, extracts the right parameters from natural language, and calls the function. The entire thing runs serverless — no EC2, no containers, no servers to babysit. By the end of this tutorial, you will have a working Bedrock Agent backed by a Lambda function that handles four HR operations: checking leave balances, submitting time-off requests, looking up company policies, and viewing team calendars. Total AWS cost to follow along: under $1. Prerequisites An AWS account with Amazon Bedrock access enabled AWS CLI v2 installed and configured ( aws configure )