About This Architecture

AI-driven retail price intelligence pipeline ingesting e-commerce and retail APIs from major Latin American chains (Tottus, Wong, Metro, Plaza Vea, Vivanda) into extraction and transformation layers. Data flows through Agentecore Runtime orchestrating Claude Haiku LLM agents with specialized tools for competitive price comparison, category universe listing, and data enrichment against SQL Server backend. Agent traces feed observability systems while homogenized output data and performance metrics flow to Laive distributor systems, enabling real-time competitive pricing decisions. Fork this diagram on Diagrams.so to customize API sources, LLM models, or add additional agent tools for your retail analytics use case.

People also ask

How do you build a real-time competitive price intelligence system using AI agents and retail APIs?

This diagram shows an end-to-end architecture where external retail and e-commerce APIs feed into extraction and transformation layers, then route through Agentecore Runtime orchestrating Claude Haiku LLM agents. Specialized tools compare competitor prices, list product categories, and enrich data before homogenization and output to distributor systems with performance metrics.