Predictive Maintenance & Financial Intelligence System
14 AI agents analyze performance data, detect anomalies, predict failures, assess financial impact, optimize schedules, and generate intelligence reports with market, ESG, and regulatory context..
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Mission Control - Portfolio selection and analysis configuration for predictive maintenance across solar and wind assets
Agent Workspace - Live multi-agent execution with data collection pipeline and real-time processing insights
Intelligence Report - Executive summary showing $762K preventable losses, 1515% ROI, and prioritized maintenance recommendations
Process Execution - Detailed agent orchestration metrics showing 6 agents, 13 tool calls, and 850K data points processed
AI Agents
Specialized autonomous agents working in coordination
Mission Orchestrator Agent
Coordinating 14 agents requires proper sequencing, parallel execution, progress tracking, and error handling.
Core Logic
Manages execution plan with parallel groups, tracks progress and cost per agent, handles inter-agent communication and handoffs, enforces configuration parameters, consolidates results with timeout and retry logic.
Data Ingestion & Preparation Agent
Analysis requires consolidated, validated data from SCADA, weather, and financial sources with temporal alignment.
Core Logic
Connects to PostgreSQL, SolarAnywhere API, SAP. Validates quality (coverage, freshness, accuracy), applies temporal alignment, calculates quality scores, prepares unified dataset with record counts and metrics.
Performance Analysis Agent
Understanding actual vs expected performance requires weather normalization and underperformer identification.
Core Logic
Calculates IEC 61724 Performance Ratio with temperature correction, computes capacity-weighted averages, identifies outliers using z-scores, compares against baselines, quantifies gaps in MWh and revenue terms.
Anomaly Detection Agent
Early degradation detection requires identifying subtle sensor patterns deviating from normal operation.
Core Logic
Applies Isolation Forest to multivariate sensor data, detects point/contextual/collective anomalies, calculates anomaly scores with confidence intervals, correlates across sensors, flags assets with degradation signatures.
Root Cause Analysis Agent
Understanding underlying causes requires causal inference rather than simple correlation.
Core Logic
Implements causal inference analyzing temporal relationships, tests hypothetical interventions, identifies confounding variables, produces ranked causes with confidence scores, supporting evidence, and verification steps.
Recommendation Engine Agent
Translating insights into actionable recommendations requires financial justification and implementation guidance.
Core Logic
Applies optimization algorithms for maintenance schedules, calculates ROI/payback per recommendation, considers resource constraints, prioritizes by financial impact, produces roadmaps with explainability factors.
Risk Assessment Agent
Portfolio managers need visibility into technical, financial, regulatory, and market risks with quantified impact.
Core Logic
Evaluates equipment failure probability, financial exposure, regulatory gaps, weather/grid risks. Calculates composite scores, generates heatmaps, identifies mitigation strategies, triggers escalation for critical risks.
Intelligence Report Generator Agent
Synthesizing multi-agent analysis into coherent reports for executives, operators, and investors.
Core Logic
Aggregates agent outputs, generates executive summary, produces detailed sections (performance, anomalies, recommendations, risks), includes visualizations, formats for PDF/Excel/JSON with corporate branding.
Energy Market Intelligence Agent
Decisions require real-time visibility into LMP prices, capacity payments, and demand response opportunities.
Core Logic
Integrates with ERCOT/PJM/CAISO APIs for real-time and day-ahead prices, monitors trends and volatility, identifies storage arbitrage, tracks demand response events, calculates revenue impact of curtailment.
ESG Scoring & Sustainability Agent
Stakeholders require ESG metrics including carbon avoided, community impact, and UN SDG alignment.
Core Logic
Calculates environmental metrics (CO2 offset, water saved), social metrics (jobs, community investment, safety), governance scores. Maps to UN SDGs, benchmarks against peers, identifies improvement opportunities.
Regulatory Compliance Agent
Assets must track IRA tax credits (ITC/PTC), state incentives, permits, and interconnection agreements.
Core Logic
Monitors IRA eligibility with bonus credits (domestic content, energy community), tracks PPA terms, manages permit renewals, validates compliance, calculates available credits, alerts on deadlines with penalty risk.
Grid Demand Forecasting Agent
Optimizing dispatch and storage requires forecasting demand, curtailment risk, and demand response value.
Core Logic
Integrates with grid operator APIs, forecasts demand (hourly to weekly), calculates renewable share and curtailment probability, monitors battery state, identifies optimal charge/discharge strategies and DR participation.
Weather Intelligence Agent
Solar generation depends on accurate irradiance, temperature, and severe weather forecasting.
Core Logic
Retrieves weather data (temperature, GHI/DNI, cloud cover), calculates production impact, generates generation forecasts, monitors severe weather alerts (hail, wind, lightning), triggers protective actions.
Carbon Credit Optimization Agent
Maximizing carbon credit revenue requires understanding market dynamics and optimal timing.
Core Logic
Tracks carbon/REC prices (voluntary and compliance markets), calculates offset using grid marginal emissions, projects revenue, identifies optimal selling timing, quantifies social cost of carbon avoided.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
1 technologies
Architecture Diagram
System flow visualization