Smart Anomaly Investigation & Resolution Digital Worker

Core Logic

Coordinates the entire investigation workflow using Claude 3 Opus with temperature 0.3 for deterministic orchestration. Validates input data, determines appropriate agent pipeline routing, manages parallel and sequential agent execution, monitors progress across 6 workflow stages, synthesizes findings from all agents into unified recommendations, and generates comprehensive audit trails with distributed tracing (traceId, spanId).

Core Logic

Scans the IoT sensor network to validate device status and data quality using real-time polling via LoRaWAN and M-Bus protocols. Monitors 192+ devices, checks battery levels and signal strength (RSSI, SNR), validates firmware versions, detects tamper alerts, and confirms data quality scores. Reports network health at 98% uptime with 94% signal quality, providing confidence that sensor readings are accurate.

Core Logic

Analyzes consumption data using Claude 3.5 Sonnet with vector store search for pattern matching. Computes statistical baselines using 7-day rolling averages, performs z-score analysis to quantify deviations (e.g., 4.7 standard deviations), identifies flow signatures matching continuous leak patterns, and calculates deviation percentages (e.g., +221% above baseline). Achieves 94% confidence through multi-source evidence correlation.

Core Logic

Runs pre-trained ML anomaly detection models (v3.2.1) with configurable thresholds (default 0.75). Classifies anomalies by type (MECHANICAL_LEAK, BEHAVIORAL, SEASONAL) with probability scores (e.g., 94%). Cross-references with seasonal patterns and occupancy data from feature stores. Distinguishes between behavioral and mechanical anomalies through flow pattern signature analysis.

Core Logic

Loads historical consumption patterns and equipment health data to run LSTM-based forecasting models. Generates 30-day consumption forecasts with 91% confidence intervals, predicts failure probabilities (e.g., 78% water leak probability), estimates time-to-failure windows (e.g., 3-day escalation window), and calculates cost-of-inaction metrics. Uses model version v2.3.1 for maintenance scheduling recommendations.

Core Logic

Fetches historical and forecast weather data from meteorological APIs. Calculates heating degree days (HDD) and cooling degree days (CDD), correlates weather patterns with consumption data using statistical models, and determines weather impact percentages (e.g., +8% heating demand due to cold front). Distinguishes weather-related consumption increases from mechanical faults through correlation coefficients (e.g., 0.03 for water-weather correlation indicating independence).

Core Logic

Uses RAG-powered search across historical case databases to retrieve similar cases (e.g., 23 similar cases from vector store). Analyzes flow rate patterns to identify signature matches (e.g., 89% match to toilet flapper valve degradation). Queries equipment databases for fixture age and maintenance history, cross-validates with building pressure sensors, and determines root cause with 94% confidence supported by multiple evidence sources.

Core Logic

Queries vendor APIs for technician availability and service costs, checks inventory systems for parts availability and pricing, calculates ROI and payback periods for multiple resolution scenarios. Generates prioritized solution options with implementation steps and risk assessments.

Core Logic

Evaluates multiple resolution scenarios using financial models with configurable discount rates. Calculates NPV over configurable horizons, determines payback periods, computes risk-adjusted returns, and models ongoing waste costs. Recommends optimal solution based on maximum NPV and shortest risk-adjusted payback.

Core Logic

Queries compliance databases to check jurisdiction-specific requirements (e.g., 24-hour tenant notification, licensed contractor requirement). Verifies contractor licenses and insurance validity against regulatory databases. Validates that proposed resolutions meet all applicable regulations and documents compliance status for audit trails. Returns clear compliance status (CLEAR/WARNING/VIOLATION) with specific requirements checklist.

Core Logic

Analyzes property carbon footprint using GHG Protocol methodology with DEFRA emission factors. Calculates CO2 savings from anomaly resolution (e.g., 24 kg CO2/year), assesses impact on energy efficiency ratings (A-G scale), and evaluates alignment with sustainability targets. Provides ESG score impact projections and green building certification implications.

Core Logic

Compiles ESG metrics using GRI and SASB standards, generating scores across Environmental (72/100), Social (81/100), and Governance (88/100) dimensions. Benchmarks against industry peers, tracks EU Taxonomy alignment for water efficiency criteria, and generates investor-ready sustainability disclosure content. Documents resolution impacts for quarterly and annual ESG reporting.

Core Logic

Reviews applicable regulations from compliance databases including HeizKVO (German Heating Cost Ordinance), EED (EU Energy Efficiency Directive), and local building codes. Identifies compliance requirements (e.g., 12 applicable requirements, 11 compliant, 1 pending), analyzes upcoming regulatory changes, and flags action items with deadlines (e.g., EED monthly reporting due in 30 days).

Core Logic

Generates personalized tenant notifications using LLM with tone optimization (professional_friendly). Analyzes tenant profiles for communication preferences (EMAIL, SMS, APP, PHONE) and preferred language. Produces messages with Grade 8 readability scores, positive sentiment (0.82), and appropriate urgency levels (0.76). Creates multi-channel notification packages with backup channels for delivery confirmation.