Multi-Agent Portfolio Energy Optimization Digital Worker

Core Logic

Manages the complete 15-agent workflow using Claude 3 Opus with temperature 0.3. Validates campaign configuration parameters, dispatches data collection requests, monitors agent progress and dependencies, coordinates parallel execution where possible (parallelization factor 0.65), and synthesizes final recommendations. Maintains comprehensive session metrics including token usage, API calls, cache hit rates, and cost tracking.

Core Logic

Uses GPT-4 Turbo with temperature 0.1 for reliable data retrieval. Connects to meter data warehouses, queries consumption data for configurable analysis periods, retrieves building characteristics from property databases, and aggregates monthly consumption patterns. Handles 175,200+ records (8,760 hourly readings × 20 buildings) with data quality validation.

Core Logic

Uses GPT-4o with temperature 0.0 for deterministic validation. Analyzes data completeness across all meters, identifies anomalies and outliers, detects data gaps requiring interpolation, validates readings against expected ranges, and calculates data quality scores (0-100%). Reports confidence levels (HIGH/MEDIUM/LOW) based on quality assessment.

Core Logic

Applies ML models using Claude 3.5 Sonnet with temperature 0.5 for comprehensive analysis. Compares consumption to ENERGY STAR benchmarks, identifies efficiency opportunities across 7 intervention categories (HVAC, lighting, envelope, controls, water, renewable, behavioral), analyzes HVAC performance indicators, and cross-references with ASHRAE 90.1 standards and industry best practices.

Core Logic

Uses GPT-4 Turbo with temperature 0.0 for precise financial calculations. Computes investment costs using regional pricing data, calculates NPV with configurable discount rates, models cash flows over configurable horizons, performs sensitivity analysis on key variables, and compares Conservative, Balanced, and Aggressive scenarios. Reports IRR, payback periods, and risk-adjusted returns.

Core Logic

Evaluates implementation complexity using Claude 3.5 Sonnet with temperature 0.2. Assesses vendor and supply chain risks, calculates confidence intervals for savings estimates, identifies items requiring human review, and generates risk mitigation recommendations. Categorizes risks by probability and impact, flagging high-risk items for stakeholder attention.

Core Logic

Uses Claude 3 Opus with temperature 0.7 for creative recommendation generation. Prioritizes opportunities based on configurable weighted criteria, generates implementation roadmaps with dependencies, creates executive summaries with key findings, compiles evidence links for all recommendations, and structures outputs across implementation phases with timeline coordination.

Core Logic

Scans real-time data streams using Claude 3.5 Sonnet with statistical deviation analysis (3-sigma rule). Detects anomalies across building portfolio, cross-references with historical baselines for validation, identifies potential water leaks requiring investigation, and calculates estimated cost impact. Classifies by severity (low/medium/high/critical) and type (consumption_spike, potential_leak, equipment_failure).

Core Logic

Loads IoT sensor health data and runs ML failure prediction models using GPT-4o with temperature 0.2. Identifies equipment with degradation patterns, calculates remaining useful life (RUL) estimates, generates maintenance schedules with priority ranking, and estimates repair vs. downtime costs. Covers HVAC, boilers, chillers, pumps, motors, meters, and sensors.

Core Logic

Fetches historical weather data using GPT-4 Turbo with temperature 0.1. Calculates heating degree days (HDD) and cooling degree days (CDD), correlates consumption patterns with temperature variations, generates weather-normalized baselines, and determines weather impact percentages on total consumption. Rates building efficiency (excellent/good/average/poor/critical) relative to weather conditions.

Core Logic

Uses Claude 3 Opus with temperature 0.0 for precise compliance checking. Loads regulatory requirements databases, checks meter remote-readability compliance (2021/2026 mandates), validates monthly consumption reporting requirements, reviews GDPR Article 30 compliance, and identifies compliance gaps. Reports overall compliance scores and penalty risk exposure.

Core Logic

Segments tenants by consumption patterns using Claude 3.5 Sonnet with temperature 0.4. Classifies into segments (eco_champion, conscious_consumer, average_user, high_consumer), compares individual usage against portfolio average, identifies high-consumption tenants with savings potential, and calculates potential annual savings from behavior change programs. Assesses engagement responsiveness for program targeting.

Core Logic

Calculates portfolio carbon footprint using Claude 3 Opus with CRREM decarbonization pathway benchmarking. Computes ESG scores across three dimensions, tracks progress toward net-zero targets, generates investor-ready sustainability disclosure reports (GRI, SASB standards), and assigns ratings (A+ through F). Reports Scope 1, 2, and 3 emissions with carbon intensity metrics.

Core Logic

Connects to live IoT sensor networks using GPT-4o Mini with temperature 0.0 for efficient processing. Monitors active meters across portfolio (186+ active streams), processes 5,000+ data points per minute, tracks portfolio health scores in real-time, and maintains system health dashboards (healthy/degraded/critical). Uses MQTT protocol for low-latency streaming.

Core Logic

Aggregates alerts from all monitoring agents using Claude 3.5 Sonnet with ML prioritization. Applies severity and impact ranking, correlates related alerts for root cause analysis, generates suggested actions for each alert, and dispatches notifications to relevant stakeholders. Categorizes by type (anomaly, leak, maintenance, compliance, efficiency, cost, esg) with priority levels 1-5.