AWS Bedrock AgentCore lets analysts build NLP dashboard automation agents

Business analysts often face multi-day turnaround times when requesting dashboard modifications through traditional IT processes. AWS introduces a solution combining Amazon Bedrock AgentCore, Strands Agents, and Amazon QuickSight to automate this with natural language queries. The multi-agent architecture consists of a Find Dashboard Agent for discovery (searching dashboards and retrieving column metadata), a Modify Dashboard Agent for execution (validating columns, updating table visuals, creating new versions), and an Orchestrator Agent that classifies user intents using Amazon Nova's NLP. Conversational queries get direct responses, while operational requests (e.g., 'Add lastname to the testing dashboard') are routed to specialized agents. The system autonomously executes changes with security controls, audit trails, and rollback preservation of original dashboards.

Implementation requires an AWS account with IAM permissions for QuickSight APIs (ListDashboards, DescribeDashboard, DescribeDataSet, CreateDashboard), Python 3.10+, the uv package manager, and AWS CLI. Users build the three agents, deploy them to Amazon Bedrock AgentCore, and test via the AWS console. Amazon Bedrock AgentCore provides intelligent memory for context, dynamic scaling, and production-grade observability—logging agent decisions and tracing API interactions. By offloading routine dashboard changes to AI, business analysts gain agility while IT teams reduce repetitive tickets. This solution is especially valuable for organizations needing fast, secure, and auditable business intelligence adjustments.