Enterprise Predictive Maintenance & Energy Optimization Platform

Core Logic

The Orchestrator implements a DAG-based workflow engine with stage-gate execution: Data Collection → Analysis → Optimization → Synthesis. It manages agent dependencies, enables parallel execution within stages, implements circuit breaker patterns for fault tolerance, and provides comprehensive execution metrics. The agent generates W3C Trace Context compatible traces for full observability.

Core Logic

The Data Ingestion Agent connects to PostgreSQL equipment databases (127+ records), Salesforce CRM (52+ accounts), SAP ERP financial systems, and Oracle WMS inventory systems. It performs schema mapping, data validation, null handling, and creates unified data models. The agent implements connection pooling, query optimization, and caching with 12ms typical latency for equipment database queries.

Core Logic

The IoT Processor subscribes to MQTT/Kafka telemetry streams, applying signal processing algorithms for noise reduction and outlier detection. It calculates rolling efficiency scores, detects anomaly patterns using statistical process control, correlates sensor readings with equipment health models, and flags devices exhibiting pre-failure signatures. Processing latency averages 45ms with high-throughput stream handling.

Core Logic

The Reliability Engine implements Weibull distribution analysis with configurable parameters (β shape, η scale). It processes equipment age, operating conditions, and failure history to calculate reliability scores R(t) = e^(-(t/η)^β). The agent supports multiple distribution types (Weibull, Exponential, Log-Normal), confidence intervals (90-99%), and historical calibration from maintenance records. It generates 30/90-day failure forecasts with probability rankings.

Core Logic

The Customer Segmentation Agent performs RFM (Recency, Frequency, Monetary) analysis combined with K-means clustering to segment customers into 6 distinct groups. It calculates customer lifetime value, identifies churn risk indicators, and generates segment-specific recommendations. The agent supports configurable segment counts (4-8) and produces segment characteristics, recommended actions, and revenue potential estimates.

Core Logic

The Route Optimizer solves the Traveling Salesman Problem (TSP) using configurable algorithms: Nearest Neighbor for speed, 2-Opt for quality, Genetic Algorithm for complex constraints, or Simulated Annealing for global optimization. It considers technician certifications, appointment time windows, equipment requirements, and real-time traffic data. The agent produces optimized routes with distance/time/cost metrics and map visualization data.

Core Logic

The Risk Analyzer performs Monte Carlo simulation with configurable iterations (1,000-100,000) using Normal, Beta, or full Monte Carlo distribution types. It calculates Value at Risk (VaR) at 95% confidence, Conditional VaR, probability of loss, and generates risk-adjusted revenue forecasts. The agent produces distribution visualizations, percentile tables, and scenario-based risk assessments.

Core Logic

The Recommendation Engine aggregates insights from upstream agents and applies prioritization logic based on configurable business weights (revenue, risk, customer value, urgency). It generates categorized recommendations (maintenance, sales, operations, efficiency), assigns confidence scores, and creates action items with owners and due dates. The agent produces executive summaries, risk alerts, and opportunity rankings.

Core Logic

The Digital Twin Engine maintains synchronized virtual models of connected equipment with real-time IoT data feeds. It supports predictive simulations (failure scenarios, performance projections), what-if analysis with variable manipulation, and accuracy tracking against actual outcomes. The agent enables risk-free testing of operational changes and generates scenario comparison reports with confidence intervals.

Core Logic

The Carbon Optimizer calculates total emissions from fleet operations, equipment energy consumption, and supply chain activities. It generates ESG scores (Environmental, Social, Governance), tracks progress toward net-zero targets, identifies reduction opportunities, and monitors compliance with EU carbon taxonomy. The agent produces sustainability recommendations categorized by implementation timeline.

Core Logic

The Smart Grid Integrator monitors grid signals and enrolled equipment capacity for demand response participation. It calculates load balancing opportunities, optimizes time-of-use scheduling, and coordinates peak shaving events. The agent tracks potential savings from shifted consumption, manages redistribution plans across zones, and maintains grid stability scores with event history.

Core Logic

The Energy Efficiency Scorer calculates energy performance scores (A-G ratings) based on consumption data, building characteristics, and regional benchmarks. It identifies underperformers, quantifies savings opportunities in kWh and EUR, and generates upgrade recommendations with investment costs, projected savings, and payback periods. The agent monitors regulatory compliance deadlines and gap analysis.

Core Logic

The Predictive Inventory Agent analyzes maintenance schedules, failure predictions, and historical usage patterns to forecast 30/90-day parts demand. It generates stock alerts (stockout risk, overstock, expiring, obsolete), evaluates supplier reliability and pricing, and creates automated reorder recommendations. The agent calculates inventory health metrics including turnover rate, carrying costs, and optimization savings potential.

Core Logic

The Weather Analyzer integrates OpenWeather API data (temperature, humidity, precipitation, wind) with HVAC demand indexes. It generates weather-adjusted demand forecasts, scheduling recommendations to avoid adverse conditions, seasonal trend analysis, and weather alerts. The agent calculates service impact levels and provides proactive rescheduling suggestions to maintain service quality.