Multi-Agent Crisis Response System
Deploys six specialized AI agents with LLM-powered analysis, agent memory and RAG for context retrieval, distributed tracing for observability, and human-in-the-loop approval workflows. Produces executive decision packages with financial projections and implementation timelines.
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Crisis management configuration interface for selecting crisis type, affected products/regions, urgency level, and agent pipeline initialization
Live agent execution showing sequential multi-agent pipeline processing with real-time output streams and distributed tracing
Technical observability dashboard displaying detailed performance metrics, execution statistics, and capabilities for all six AI agents
Executive decision dashboard for stock-out crisis with risk assessment, recommended actions, financial impact analysis, and approval workflow
AI Agents
Specialized autonomous agents working in coordination
Inventory Analyst Agent
During crises, inventory positions across warehouses, in-transit stock, and committed orders must be rapidly assessed to understand available supply for response actions.
Core Logic
Analyzes real-time inventory levels, depletion rates, safety stock positions, and warehouse locations. Calculates days of supply, identifies redistribution opportunities, and recommends emergency reorder quantities with supplier lead times.
Demand Forecaster Agent
Crisis situations often involve demand uncertainty requiring rapid forecast updates that incorporate new market signals, weather impacts, and competitive dynamics.
Core Logic
Updates demand forecasts using time-series models, seasonal adjustments, and real-time market signals. Integrates weather forecasts, commodity prices, and competitor activity to produce revised demand projections with confidence intervals.
Logistics Optimizer Agent
Emergency fulfillment requires optimized routing, fleet allocation, and delivery scheduling that may differ significantly from standard operations.
Core Logic
Optimizes delivery routes using vehicle routing algorithms, allocates fleet resources based on capacity and location, and creates priority delivery schedules. Considers driver hours, fuel costs, and customer priority tiers.
Risk Assessor Agent
Crisis response actions carry their own risks including cost overruns, customer impact, supplier relationship strain, and operational disruption requiring systematic evaluation.
Core Logic
Evaluates risk factors for proposed response actions using likelihood-impact scoring. Models scenario outcomes, identifies mitigation strategies, and calculates risk-adjusted expected values for decision support.
Decision Synthesizer Agent
Multiple agent analyses must be synthesized into coherent recommendations that balance inventory, demand, logistics, and risk considerations with business constraints.
Core Logic
Integrates outputs from all specialist agents using multi-criteria decision analysis. Resolves trade-offs, applies business constraints, and generates prioritized action plans with resource requirements and success probabilities.
Communication Specialist Agent
Crisis situations require coordinated stakeholder communications to customers, sales teams, suppliers, and leadership with appropriate messaging for each audience.
Core Logic
Drafts stakeholder-specific communications based on crisis context and recommended actions. Creates customer notifications, sales team briefings, supplier requests, and executive updates with appropriate tone and detail level.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
6 technologies
Architecture Diagram
System flow visualization