🚛 AINNA NeuralOps · Logistik

AI-Powered Logistik Operasi

Detached AI systems for fleet management, warehouse operations, route optimisation, last-mile delivery, inventory control, customs, driver safety, cargo monitoring, yard management, and demand forecasting. Run locally, controlled by you.

Terokai Sistem View Kes Penggunaan Hubungi Kami
10Sistem Teras
8Kes Penggunaan
100%On-Premise

Semasa: Smart routing + detached systems + private infrastructure are production-ready for suitable workloads (internal 87% token benchmark on tested patterns).
Peta Hala Tuju: Larger inference clusters and deeper autonomous layers are Phase 2 (funding-dependent). Lihat Roda Tenaga Kecekapan →

Live Supply Chain Flow

From order signal to proof of delivery

A logistics control loop for warehouse pick, route optimisation, driver dispatch, and delivery confirmation.

Stage 0 / 5 · Sedia 0%
Order queue live…
01 Order Jualan order ingested Menunggu
02 Gudang Pick Wave pick confirmed Menunggu
03 Route Optimise ETA & fuel model Menunggu
04 Driver Dispatch App push + geofence Menunggu
05 POD Proof of delivery Menunggu
ETA risk Rendah
Fuel saving 0%
Cargo status Staging
Site Event Log LANGSUNG
// Route Optimiser waiting for Main…
Sistem Teras

Logistik Sistem Berasingan

AI-powered systems that monitor, optimise & automate supply chain operations all running on your own infrastructure.

Fleet Pengurusan

Real-time GPS tracking, vehicle utilisation & fuel management.

GPS Utilisation Fuel Asset
▶ Demo Senario

Operasi Gudang

Slot optimisation, pick-path routing & dock scheduling.

Slots Pick Path Dock WMS
▶ Demo Senario

Route Optimisation

AI-driven multi-stop routing with traffic & weather overlays.

Penghalaan Traffic Weather Multi-Stop
▶ Demo Senario

Last-Mile Delivery

Pelanggan-noted delivery windows, proof of delivery & ETA.

ETA POD Window Pelanggan
▶ Demo Senario

Kawalan Inventori

Stok levels, reorder points & ABC analysis across laman.

Stock Reorder ABC Multi-Site
▶ Demo Senario

Customs & Rentas Sempadan

Dokumentasi, HS code classification & duty calculation.

Docs HS Code Duty Border
▶ Demo Senario

Driver Keselamatan

Behaviour monitoring, fatigue scoring & coaching feedback.

Behaviour Fatigue Coach Skor
▶ Demo Senario

Cargo Pemantauan

Temperature, humidity, shock & tamper sensing in transit.

Temp Humidity Shock Tamper
▶ Demo Senario

Yard Pengurusan

Gate check-in, trailer tracking & dock door assignment.

Gate Trailer Dock YMS
▶ Demo Senario

Demand Forecasting

AI demand models with seasonality & promotional lift.

Ramalan Seasonality Promo AI Model
▶ Demo Senario

These are the Sistem Berasingan layer. AI helps design and improve via the Kecekapan Flywheel (segment → route → distil). The running system uses normal software — zero tokens at execution time. Full flywheel →

Keselamatan & Pematuhan

Keselamatan Sistem Pengurusan

Comprehensive safety tracking for logistics operations driver fatigue, vehicle inspection, hazmat, loading safety, workplace safety, emergency response, incident reporting, and security.

Driver Fatigue

Hours-of-service tracking & alert scoring.

HOS Alert Skor

Vehicle Pemeriksaan

Pre-trip & post-trip defect capture.

Pre-Trip Defect Capture

Hazardous Materials

Hazmat classification & placard check.

Class Placard Segregation

Loading Keselamatan

Weight distribution & securement audit.

Weight Securement Audit

Workplace Keselamatan

Gudang hazard & near-miss logging.

Hazard Near-Miss Log

Emergency Response

Spill, accident & breakdown protocol.

Spill Accident Protocol

Laporan Insidening

Capture, investigate & trend incidents.

Capture Investigate Trend

Keselamatan

Cargo theft prevention & access control.

Theft Access Track
Kes Penggunaan

Logistik Kes Penggunaan

Real-world applications of AI detached systems in logistics and supply chain operasi.

Fleet Tracking

Real-time GPS tracking & vehicle utilisation across the fleet.

GPS Utilisation Fuel Asset

Automasi Gudang

Slot optimisation, pick-path routing & dock scheduling.

Slots Pick Path Dock WMS

Route Perancangan

AI-driven multi-stop routing with traffic & weather overlays.

Penghalaan Traffic Weather Multi-Stop

Last-Mile

Pelanggan-noted delivery windows, proof of delivery & live ETA.

ETA POD Window Pelanggan

Customs Kepatuhan

Dokumentasi, HS code classification & duty calculation.

Docs HS Code Duty Border

Inventori Optimisation

Stok levels, reorder points & ABC analysis across laman.

Stock Reorder ABC Multi-Site

Driver Pemantauan

Behaviour monitoring, fatigue scoring & coaching feedback.

Behaviour Fatigue Coach Skor

Cargo Visibility

Temperature, humidity, shock & tamper sensing in transit.

Temp Humidity Shock Tamper
Manfaat

Mengapa AINNA untuk Logistik

Transform your supply chain operations with AI-powered detached systems.

🚛

On-Premise

Semua sistem berjalan pada infrastruktur anda sendiri. Tiada kebergantungan pada awan, dan tiada data meninggalkan premis anda.

🤖

AI-Powered

LLM Persendirian (Qwen, DeepSeek) processes data locally with intelligent automation.

📊

Real-Time

Live monitoring of fleet, warehouse, route & cargo operasi.

🔒

Selamat

ISO-compliant, audit-ready, with full traceability and access control.

💰

Kos Efektif

Reduce operational costs through optimised routes, fuel, and inventory.

🌿

Mampan

Emission tracking, fuel optimisation & green logistics compliance.

NeuralOps

How the Kecekapan Flywheel Applies to Logistik

Segmentation → Smart Routing → Distillation → Sistem Detached Sistem → Infrastruktur Swasta.

Example: A fleet fuel & route job is segmented into format checks, rule-based exceptions, and optimisation. Most cases route to deterministic engines. High-volume pattern matching (e.g. recurring delay signatures) can be distilled into a small specialist model. The final dispatch, proof-of-delivery, and billing updates run as a detached system with zero token cost after build.
87% pengurangan token is an internal benchmark on tested workloads. See full flywheel · distillation · routing strategies.
ESG Impak

Jejak Karbon Reduction

Illustrative design objectives based on internal modelling for a representative logistics operation.

🔴

Before NeuralOps

80,000
tCO₂e / year
Garis Dasar emissions from Logistik operations
🟢

After NeuralOps

56,000
tCO₂e / year
Operasi dioptimumkan dengan kecekapan dipacu AI.
💚

Total Reduction

24,000
tCO₂e / year
30% decrease in carbon intensity
🚛 Route Optimization
−12,000 tCO₂e/year
⛽ Fuel Kecekapan
−8,000 tCO₂e/year
📦 Load Optimization
−4,000 tCO₂e/year

Carbon figures shown are illustrative design objectives based on internal modelling for a representative logistics operation. Actual results depend on baseline, grid factors, and measured data. See ESG methodology.

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Updated Nov 8, 2026 10:19 PM

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