14:00 | 26/02/2021 Companies
(VEN) - Shelev Vietnam, a vision driven fleet and technology ecosystem provider for Vietnam’s transport industry plans to offer a subscription-based next-generation transport management system using AI.
From left: Tran Van Hien, Mobility Manager; Merlin Gerhard Kwan, Co-founder & Executive Director; Nghia Huynh, Associate Director
The company plans to deploy an AI engine that structures data algorithms in layers, forming an artificial neural network. The engine will source additionally from alternative data sources via connected IOT devices and incentivized crowd-sourced data.
The new transport management platform with latest deep technology at its core will provide significantly improved efficiencies and cost savings for customers’ trucking operations in Vietnam.
The environmentally conscious company has already been offering customized fleet solutions for the latest future-ready clean and green fleets since early 2018 – Euro 6 & 4 emission standard, CNG, and electric vehicles, such as trucks, taxis, cars, buses, and material-handling equipment.
Shelev’s network of fleet customers includes multinational and local logistics enterprises, manufacturers, trading companies, taxi networks and public transport operators.
“Deep-tech is entering the supply chain and transport sector and will have a profound impact on our customers’ businesses,” said Shelev Vietnam Executive Director Merlin Gerhard Kwan.
He also said that the company aims to become the leader in developing an innovative fleet and technology ecosystem that meets the unique needs of Vietnamese fleet owners.
The new proprietary system will use a cutting edge deep-tech engine that is self-learning, autonomous, and can make intelligent planning decisions on its own.
Shelev’s fleet customers will receive the pre-installed system as an on-board service with existing fleet solutions. Additionally, for their own fleet vehicles, customers can utilize the subscription-based platform via cloud-based apps.
The new AI-platform aims to improve the efficiency of its customer transport operations, manpower and asset allocations, and complex planning decisions – resulting in efficiencies and savings of up to 40%.
Currently, available transport management software solutions can be defined as input based digital online job planning tools, but these lack deep-learning integration, alternative data sources and autonomous decision-making.
“Currently available trucking transport management software doesn’t solve the deep-rooted issues that deep-tech can potentially solve today,” said David Yeo, CEO of Innovez One – a leading machine-learning and artificial intelligence systems provider in the port and marine transport sector.
As a first sector focus of the system, Shelev aims to address the needs of the container trucking segment and plans to launch product trials latest by 2022. At least two current multinational customers have confirmed interest in participating in the development trials.