From zero-shot forecast to purchase order with Amazon Bedrock AgentCore

This article describes an end-to-end inventory automation pipeline that combines Amazon Chronos2 for zero-shot demand forecasting with multi-agent orchestration on Amazon Bedrock AgentCore to convert forecasts into validated purchase orders with full auditability.

• Chronos2 performs zero-shot time-series forecasting without per-product model training, supporting past and future covariates for conditional predictions
• Four LLM agents (Supervisor, Preprocessing, Forecasting, Reporting) coordinate deterministic tools to apply business rules, validate constraints, and generate audit trails
• Achieved 12.3% median WAPE on 50 SKUs, reduced onboarding from 2–3 weeks to under 5 minutes, and cut monthly inference cost 98% ($1,091 to $15) using SageMaker Serverless
• Multi-agent design isolates context windows, enables component-level testing, and treats constraint violations as workflow states requiring user input rather than silent failures
• AgentCore services (Runtime, Gateway, Policy, Memory, Observability, Evaluations) each address one production concern: execution isolation, authorization, session persistence, auditability, and quality monitoring
• Two-layer evaluation framework: LLM-as-a-Judge for agent behavior compliance, code-based Lambda evaluator for forecast accuracy (WAPE, bias, pinball loss, coverage)

The architecture demonstrates that zero-shot forecasting and multi-agent automation remove operational burden by eliminating per-SKU model training and enabling business rule changes without code deployment.