About This Architecture

Automated Insights Engine powered by an AI Agent Architecture using LangGraph-style orchestration to generate business intelligence from multi-source product data. The system routes inputs through an API Gateway with WAF and authentication, then deploys specialized agents—Planning, Drilldown, Filter Normalization, Stopping Criteria, and Root-Cause—coordinated by an Agent Controller to progressively extract and rank insights. Analysis modules including Year-over-Year, Pareto, and Peer Comparison feed a semantic embedding service backed by vector DB for insight deduplication and history tracking. Results flow through an Insight Formatter to REST/Webhook outputs and an async event bus, with full audit logging and monitoring integration. Fork this diagram to customize agent workflows, add domain-specific analysis modules, or adapt the state machine for your insight generation pipeline.

People also ask

How do I architect an AI agent system to automatically generate business insights from multiple data sources?

This diagram shows a production-grade AI Agent Architecture using LangGraph orchestration where specialized agents (Planning, Drilldown, Filter Normalization, Root-Cause) coordinate through an Agent Controller to progressively extract insights. Pluggable analysis modules (Year-over-Year, Pareto, Peer Comparison) feed a semantic embedding service with vector DB for deduplication, while a workflow s