AI Agentic Crisis Intervention System
Deploys an **8-agent orchestration system** that continuously analyzes project portfolios, predicts crisis scenarios using Bayesian probability and Monte Carlo simulations, and autonomously generates intervention recommendations with quantified ROI and success probability metrics..
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
AI Agentic Mission Control - Configure target project with health score, budget tracking, identified risks, and connected data sources for crisis analysis
AI Agent Orchestration - Real-time workflow progress tracking with agent communication stream and chain-of-thought reasoning visualization
Analysis Summary - Critical findings dashboard showing budget overrun, velocity decline, skill gaps, and technical debt issues with severity indicators
Recommendations View - AI-generated intervention strategies with ROI projections, success probability, and impact analysis for crisis resolution
AI Agents
Specialized autonomous agents working in coordination
Maestro - Orchestrator Agent
Complex multi-agent workflows require intelligent coordination to prevent conflicts, optimize task sequencing, and ensure coherent crisis response across diverse specialized agents.
Core Logic
Powered by **GPT-4 Turbo**, Maestro decomposes complex tasks into subtasks, routes them to appropriate specialist agents, and resolves conflicts through consensus mechanisms. Equipped with **Task Planner** and **Agent Router** tools, it maintains workflow coherence and manages inter-agent handoffs with priority-based scheduling.
Insight - Data Analyst Agent
Project data is scattered across multiple systems, making it difficult to identify patterns, anomalies, and early warning signs of project health deterioration.
Core Logic
Utilizes **GPT-4 Turbo** with specialized tools: **SQL Query Engine** for data aggregation, **Trend Analyzer** for pattern recognition, and **Anomaly Detector** for statistical outlier identification. Performs trend analysis, correlation detection, and predictive modeling on historical project metrics.
Guardian - Risk Assessor Agent
Risk assessment is often subjective and fails to quantify the probability and impact of potential project failures, leading to under-resourced mitigation efforts.
Core Logic
Employs **GPT-4 Turbo** with **Bayesian Risk Scorer** for probability calculation, **Monte Carlo Simulator** for outcome modeling, and **EVM Calculator** for earned value analysis. Generates quantified risk scores with confidence intervals and impact projections.
Allocator - Resource Optimizer Agent
Resource allocation decisions are made without considering skills compatibility, availability conflicts, and cost optimization, resulting in team inefficiencies and project delays.
Core Logic
Powered by **GPT-4 Turbo** with **Skill Matcher** for competency alignment, **Calendar API** for availability verification, and **Cost Optimizer** for budget-aware staffing. Recommends optimal team compositions based on weighted scoring across multiple criteria.
Herald - Communicator Agent
Crisis communication is delayed, inconsistent, and poorly targeted, leading to stakeholder confusion and erosion of trust during critical project situations.
Core Logic
Uses **GPT-4 Turbo** with **Email Composer** for professional messaging, **Slack API** for real-time notifications, and **Tone Analyzer** for audience-appropriate communication. Generates context-aware communications tailored to stakeholder roles and urgency levels.
Actuator - Executor Agent
Approved intervention actions require manual implementation across multiple systems, causing delays and inconsistent execution of crisis response plans.
Core Logic
Leverages **GPT-4 Turbo** with direct integrations: **Jira API** for issue management, **Azure DevOps API** for sprint modifications, and **Calendar Updater** for schedule adjustments. Executes approved actions with audit logging and rollback capabilities.
Oracle - Predictive Analyst Agent
Traditional analytics are retrospective, identifying problems only after they manifest rather than forecasting future states and enabling preventive intervention.
Core Logic
Powered by **Claude 3.5 Sonnet** with **ML Forecaster** for time-series prediction, **Scenario Modeler** for what-if analysis, and **Anomaly Engine** for early warning detection. Generates predictive insights with confidence scores for risk, opportunity, and trend categories.
Sage - RAG Knowledge Agent
Institutional knowledge about past project crises and successful interventions is trapped in documents and tribal knowledge, making it inaccessible for current decision-making.
Core Logic
Utilizes **Claude 3.5 Sonnet** with **Vector Search** for semantic retrieval, **Knowledge Graph** for relationship mapping, and **Doc Synthesizer** for context compilation. Retrieves and synthesizes relevant historical cases to inform intervention strategies.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
4 technologies
Architecture Diagram
System flow visualization