Technology

A physics + math + AI fusion academic-grade engine.
A technology moat that's hard to replicate.

Theoretical Foundations

🧮

Why Bidirectional Modeling?

Traditional supply chain models use manually written one-way equations. Real supply chains are complex systems with bidirectional interactions — inventory feedback, capacity backpropagation. WARP adopts bidirectional modeling: just define component connections and hundreds of coupled equations are automatically derived.

⚖️

Principle of Least Action

Applying physics' Least Action Principle to business: Lagrangian ≈ Revenue − Cost = Profit. Within constraints (capacity, lead time, safety stock), the engine automatically finds the operational path that maximizes profit.

🔬

Conservation Law Verification

Like conservation of mass in physics, quantity conservation: Production = Shipments + ΔInventory is mathematically guaranteed (error 4.5×10⁻¹³). In bidirectional modeling, violations are structurally impossible.

🎯

3 Planning Modes

① Baseline PSI — simulate current conditions. ② Optimization PSI — Lagrangian-based auto-optimization. ③ Scenario PSI — What-if analysis. All three run on the same engine; parameter changes reflect in ~3ms.

Engineering

Industrial-grade simulation engine and optimization infrastructure

🔬

Supply Chain Modeling Library

In-house component-based modeling library — composable modules for inventory, production, flow, resources, and more, enabling arbitrary supply-chain network configurations. Automatic derivation of coupled equations.

Native Engine
🏗️

Industry Simulation Builder — 4 Manufacturing Types

Industry-specific simulation builder — supports discrete (assembly), continuous (chemical), batch (pharma), and project-based (construction/shipbuilding) manufacturing. Industry-specific operational patterns applied automatically on a unified engine.

Multi-Industry
📈

Sparse Matrix Acceleration

Large-scale dynamic systems with hundreds of state variables accelerated 10x+ via sparse matrix computation and symbolic caching. Real-time analysis and scenario discussion.

High Performance
🏭

Hybrid MRP II + Dynamic Simulation

MRP II material/capacity/financial planning + dynamic simulation unified bidirectionally. Multi-layer capacity scaling (equipment × policy × material constraints) + Work Calendar + 2-shift system.

MRP II · CRP
🎛️

Adaptive Inventory Policy

Multi-dimensional inventory control based on time constants, perception delay, and response intensity. Proactive demand-forecast-driven response with smooth policy transitions for oscillation-free stable operations.

Inventory Optimization
💰

Bottom-Up Cost Engine

Process-level unit cost (variable) → line → model → factory → enterprise aggregation. Internal consumption and SGA reflected for true bottom-up costing.

Cost Engine
🔗

S&OP / BPM Engine

Monthly S&OP cycle fully integrated as BPM. Demand consensus → supply review → P&L comparison → executive decision. Automated email notifications + Gate Review + Audit Trail.

S&OP · BPM
📊

Work Order + Gantt Chart

2-shift system, skill-based labor assignment, BOM material requirements. Large-scale backward planning + line-model allocation Gantt visualization.

Scheduling
🎲

Risk-Aware Optimization

Probabilistic optimization that guarantees stable returns under demand uncertainty. Multi-objective exploration auto-analyzes cost·service trade-offs.

Stochastic Opt

Optimization Engines

Three engines auto-selected or manually chosen based on problem characteristics

💫

Global Search Optimization

Multiple operational parameters (inventory, capacity, allocation, etc.) auto-tuned by swarm intelligence. Early-convergence detection for practical-time optima.

Baseline+
🎯

Precision Tuning

Local precision search using global-search results as starting point. Confidence-interval guided exploration focuses on promising regions.

High Precision
🧠

Ultra-Fast Approximation

Statistical surrogate models approximate the simulation. Optima found in tens of seconds. Autonomous learning ensures both speed and precision.

Tens of seconds
+ Approximate Optimization — Statistical surrogate model-based approximate optima search. Fast exploration followed by precision simulation verification.

Demand Forecasting Engine

16 models compete to auto-select the best forecast

Exponential Smoothing

  • SES
  • Holt
  • Damped Holt
  • HW Additive
  • HW Multiplicative

Time Series

  • ARIMA
  • SARIMA
  • Moving Avg
  • Linear Trend
  • Croston

Machine Learning

  • Ridge Regression
  • (feature-based)

Ensemble

  • AICc Weighted
  • Equal Weighted
  • Auto Select

📋 4-Stage Workflow

1. Statistical — Auto-select from 16 models (AICc)
2. Override — Sales/marketing manual adjustment
3. Consensus — Agreed forecast finalization
4. Sensing — Real-time external signal integration

📊 Additional Features

ABC-XYZ Classification — Revenue contribution × demand variability matrix
FVA (Forecast Value Add) — Accuracy contribution measurement per stage
External Signals — Economic indicators, weather, promotions integrated
ML Ridge — Signal feature-based forecast adjustment

ERP Integration

Seamless data exchange with existing systems

📥 Import / Export

4 Formats — CSV, XLSX, XML, JSON
6 Entities — Products, demand plans, BOM, orders, forecasts, signals
Validation Engine — Type, required fields, range, FK, duplicate auto-validation
Template Generation — Entity-specific templates with sample data

🔄 EDI Automation

FileWatcher — Directory monitoring → auto-import
SFTP Connector — Remote server file exchange
Field Mapping Engine — External ERP fields → WARP auto-mapping + transformation
Scheduler — Cron-based periodic exchange + retry

🔌 Plug & Play

Customer data → WARP simulation environment, auto-built in hours

PREP

Customer Environment Survey

⏱️ 15 min

Online survey to assess ERP system, database, product structure, and key challenges

• System environment diagnostic• Data availability check• Industry pre-classification
S1

Auto Schema Discovery & Mapping

⏱️ ~10 sec

Connect to customer DB and automatically scan table structures, mapping to WARP entities

• Multi-layer heuristic matching engine• Core entities auto-identified + relationship inference• High-accuracy auto-mapping with manual review UI
S2

Auto-Calibration

⏱️ ~0.1 sec

Detect industry type and infer simulation parameters from mapped data

• Automatic industry detection (manufacturing, chemical, retail, etc.)• 16 parameters inferred from data• Demand patterns, lead times, cost structures auto-learned
S3

Auto-Build Pipeline

⏱️ ~1 sec

One-click simulation environment build — data ETL + engine config + validation

• FK dependency order auto-resolved• 6-step sanity validation (products, factories, BOM, pricing, margin)• Works with DB connection or just Excel/CSV files
📂

No DB Required

Upload 3-4 Excel/CSV files and get a simulation environment instantly

✏️

Mapping Review UI

Visually review auto-mappings and fix with dropdown selectors

100x Faster

Traditional: 3-6 months → WARP: hours. Same-day simulation results

Measured Performance

Real factory data benchmarks

745+
State Variables
All inventory, production, cost tracked
2,600+
Monitoring Metrics
Revenue, profit, utilization, etc.
~1.5s
Simulation
Full factory, 26-week horizon
~19s
Auto-Optimization
AI approximate optimization
~50ms
MRP II Calculation
BOM expansion + capacity + order planning
~3ms
Parameter Change
Instant scenario switch
90+
API
Endpoints, OpenAPI documented
130+
Dashboards
Production, finance, materials, optimization, AI, Project
1,123
Tests
Engine, forecast, MRP II, Multi-DB, integration

Architecture

3-Tier Architecture
Client → Reverse ProxyAPI Gateway (Auth + Routing) → Message BusEngine

Why 3-Tier?

WARP's 3-Tier architecture is designed so each layer can be independently replaced. Whatever the customer's existing infrastructure — DBMS, middleware, message bus — WARP adapts flexibly, allowing adoption without replacing existing systems.

Tier 1 — API Gateway

Handles auth, routing, and rate limiting. Can sit on top of existing API gateways (Kong, AWS API Gateway) or reverse proxies (Nginx, HAProxy).

Tier 2 — Message Bus

Async communication between engine and API gateway. Integrates with your existing message infrastructure (RabbitMQ, Kafka, AWS SQS, etc.).

Tier 3 — Engine

Simulation and optimization compute engine. Connects directly to PostgreSQL, Oracle, SQL Server, MySQL. Supports on-premise and cloud.

🔷
Engine
ODE simulation + optimization
🤖
AI Copilot
Natural language ops + RAG + alerts
🔌
Plug & Play
One-click data onboarding
🟢
API Gateway
Auth + routing + messaging
🟠
Dashboard
130+ real-time dashboards
🐘
DBMS
Adapts to customer environment

Security & Infrastructure

🔐

Auth & Access

JWT token authentication, role-based access control (RBAC), audit logs. Handled centrally at the API gateway.

🌐

Network Security

Cloudflare tunnel + Access dual protection, bot defense, WAF, automatic DDoS mitigation.

💾

Data Isolation

Complete DB isolation per customer, encrypted storage, scheduled auto-backups, migration management.

Request Technical Consultation