Multi-Agent Risk Analysis System
Deploys specialized AI agents for each risk dimension that collaboratively analyze project documents (BIM models, schedules, budgets, geotechnical reports, environmental assessments, contracts), identify cross-cutting risk patterns, and generate comprehensive executive reports with prioritized mitigation strategies..
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Mission Control for project configuration and multi-document ingestion with real-time extraction metrics for comprehensive risk analysis
Agent Deployment showing 8 specialized AI agents for technical, financial, regulatory, environmental, schedule, and operational risk assessment
Live Analysis Console with real-time multi-agent collaboration, ESG compliance assessment, and risk identification across severity levels
Executive Intelligence Report with comprehensive risk metrics, 72 overall risk score, and prioritized mitigation recommendations
AI Agents
Specialized autonomous agents working in coordination
Technical Risk Analysis Agent
Engineering projects contain technical risks embedded in BIM models, geotechnical data, and design specifications that require specialized expertise to identify and quantify.
Core Logic
Uses Claude 3 Opus to analyze BIM models (847+ elements per model), geotechnical reports (borehole data, soil conditions), and structural specifications. Identifies design conflicts, material risks, constructability issues, and technical uncertainties with confidence-scored assessments and mitigation recommendations.
Financial Risk Analysis Agent
Project budgets contain hidden cost risks including inadequate contingencies, unrealistic assumptions, market volatility exposure, and cash flow timing issues that threaten project viability.
Core Logic
Employs GPT-4 Turbo to analyze budget estimates, cost breakdowns, contingency allocations, and contract financial terms. Identifies cost overrun risks, evaluates contingency adequacy against project complexity, and models financial scenarios with probability-weighted outcome distributions.
Regulatory Risk Analysis Agent
Projects must comply with evolving regulatory frameworks across environmental, building code, and sector-specific requirements—non-compliance can halt projects indefinitely.
Core Logic
Leverages Claude 3 Sonnet to cross-reference project parameters against Dutch regulatory databases (Omgevingswet, Bouwbesluit). Identifies permit gaps, compliance timeline risks, and regulatory change exposure. Generates compliance roadmaps with milestone dependencies and early warning indicators.
Environmental Risk Analysis Agent
Environmental impact assessments may contain unaddressed risks related to Natura 2000 proximity, protected species, contamination, and nitrogen deposition that can trigger permit rejection or project redesign.
Core Logic
Uses Claude 3 Sonnet to analyze environmental impact assessments, ecological surveys, and contamination reports. Identifies gaps in baseline studies, evaluates mitigation measure adequacy, and flags environmental red flags with quantified risk scores. Integrates with AERIUS data for nitrogen deposition validation.
Schedule Risk Analysis Agent
Project schedules often contain optimistic assumptions, unidentified dependencies, and insufficient float that lead to delays cascading through the critical path.
Core Logic
Employs GPT-4 Turbo to analyze MS Project schedules (847+ tasks), identify critical path vulnerabilities, evaluate task duration assumptions, and detect missing dependencies. Performs Monte Carlo-style scenario analysis to quantify schedule risk exposure and recommend buffer strategies.
Operational Risk Analysis Agent
Operational risks spanning resource availability, stakeholder management, communication breakdowns, and organizational capacity are often overlooked in traditional risk assessments.
Core Logic
Uses Gemini Pro to analyze project organization structures, stakeholder registers, communication plans, and resource allocation. Identifies single points of failure, stakeholder alignment risks, and organizational capacity constraints. Recommends governance improvements and contingency planning measures.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
7 technologies
Architecture Diagram
System flow visualization