Fleet & Inventory Intelligence System

Core Logic

Coordinates all specialized agents through mission-based execution. Delegates fleet analysis to the Fleet Health Analyst, inventory analysis to the Inventory Optimizer, and synthesizes findings into actionable recommendations. Resolves conflicts between agent recommendations, identifies cross-domain patterns (e.g., high brake failure predictions coinciding with low brake pad inventory), and generates comprehensive reports for executive decision-making.

Core Logic

Analyzes vehicle telemetry data using Weibull distribution (beta, eta parameters) to calculate failure probabilities. Computes Mean Time Between Failures (MTBF) for critical components. Generates risk assessments with confidence scores, estimated costs (proactive vs reactive), and evidence chains explaining predictions. Identifies vehicles requiring immediate attention with specific maintenance recommendations.

Core Logic

Calculates Economic Order Quantity using the formula sqrt(2DS/H) for optimal order sizes. Computes safety stock levels using Z-scores for target service levels (e.g., Z=1.65 for 95%). Applies exponential smoothing with seasonal adjustments for demand forecasting. Generates reorder, transfer, and clearance recommendations with expected savings calculations.

Core Logic

Correlates predicted maintenance events with parts availability across locations. Plans optimal inter-location transfers with route optimization to minimize logistics costs. Schedules services to align with parts delivery windows and service center capacity constraints. Ensures 100% service coverage for predicted maintenance events.

Core Logic

Calculates Total Cost of Ownership (TCO) comparisons between proactive and reactive approaches. Computes ROI percentages, payback periods, and Net Present Value (NPV) for recommended actions. Generates executive-ready business cases with impact breakdowns across maintenance costs, stockout incidents, inventory carrying costs, and emergency orders.

Core Logic

Continuously monitors supplier health scores across on-time delivery, quality rating, price competitiveness, responsiveness, and financial stability. Detects early warning signs and risk indicators. Benchmarks current prices against market averages and competitor pricing. Recommends supplier diversification, renegotiation, or switching based on performance trends.

Core Logic

Applies LSTM neural networks and Prophet ensemble models to forecast demand with 90%+ confidence. Incorporates external signals including weather forecasts, seasonal factors, economic indicators, and fleet growth patterns. Predicts demand surges (e.g., 34% increase in brake components during wet season) to enable proactive inventory positioning.

Core Logic

Autonomously generates purchase orders when stockout risk exceeds thresholds. Selects optimal suppliers based on health scores, pricing, and lead times. Routes orders for approval based on value thresholds (auto-approve under defined limits, escalate larger orders). Learns from past decisions to improve supplier selection over time. Provides negotiation suggestions for bulk discounts and payment terms.

Core Logic

Predicts warranty-eligible failures based on component patterns and coverage status. Scans OEM technical bulletins (TSBs) and recall campaigns, matching them to fleet VINs. Calculates potential claim values and net savings from proactive claims. Identifies vehicles eligible for manufacturer reimbursement and schedules warranty work during planned maintenance windows.