AI intelligence for
supply chain operations
Advanced AI for demand forecasting, network optimization, and autonomous logistics
The platform
Intelligent systems for supply chain optimization and logistics
Transform operations with AI
The Tenzro Supply Chain Intelligence platform combines Graph Neural Networks for network modeling, LSTM with attention for demand forecasting, and Reinforcement Learning for route optimization.
From demand prediction to last-mile delivery. Automatically optimized, validated, and deployed across distributed supply networks.
Network optimization
Graph Attention Networks model supply relationships for inventory optimization and bottleneck detection.
Demand forecasting
Hybrid LSTM with attention achieves 92.5% accuracy by analyzing sales, promotions, and macroeconomic indicators.
Route optimization
Reinforcement Learning with meta-adaptation achieves 7% improvement in path planning for dynamic routing.
AI model architectures
Production-ready models for supply chain intelligence
Supply Modeler
Graph Attention Network for supply network modeling. Heterogeneous nodes for products, suppliers, warehouses, and customers.
Demand Forecaster
Bidirectional LSTM with attention for demand forecasting. Multi-variate time series with 92.5% accuracy.
Route Optimizer
Reinforcement Learning for dynamic route optimization. GNN encoder with meta-learning for rapid adaptation.
Analyzer
Large Language Model for strategic scenario analysis. Reduces analysis time from days to minutes.
Core capabilities
AI-powered insights for supply chain excellence
Network optimization
Graph Neural Networks analyze supply relationships to optimize inventory levels, detect bottlenecks, and improve resilience across distributed networks.
Demand forecasting
7-day ahead predictions with 92.5% accuracy by analyzing historical sales, promotional activity, and macroeconomic indicators through hybrid LSTM architecture.
Route optimization
Dynamic vehicle routing with time windows achieves 7% improvement in path quality and 92.29% coverage through reinforcement learning with meta-adaptation.
Scenario analysis
LLM-powered strategic insights for demand surges, supplier disruptions, and capacity planning reduce analysis time from days to minutes.
The workflow
From network design to autonomous operations
Define network topology
Configure suppliers, warehouses, customers, and transportation links. Define constraints, capacities, and operational rules.
Model training
Graph Neural Networks learn network structure, LSTM models capture demand patterns, and RL agents optimize routing strategies.
Real-time forecasting
Generate 7-day demand forecasts with confidence intervals. Update predictions daily based on latest sales and market indicators.
Optimization & execution
Compute optimal inventory levels, route plans, and resource allocation. Execute decisions through automated workflows.
Monitor & adapt
Track KPIs, detect anomalies, analyze scenarios. Continuously improve models with operational feedback.
Deploy AI intelligence for
supply chain operations
Graph Neural Networks, LSTM forecasting, RL optimization.
Production-ready, scalable, API-first.