Unleash your Logistics Data Power
We’re experienced in breakthrough traditional logistics bottlenecks, and utilizing ML (Machine Learning) methodology for Smart Logistics!
Key Goals:
Instant Dynamic Analysis – Synchronize and centralize the logistics statuses at one dynamic dashboard in nearly real-time!
Enhanced Predictive Analysis – Mixed more different data together for an accurate and deeper logistics analysis.
Route/Process Optimization – Machine Learning helps to analyze the optimized planning for time and cost reduction.
Cooperation Performance – Understand your partners/agents’ performance and then refine the best cooperation arrangement.
Smart Logistics – Modularized Machine Learning helps discover valued business insights and best practices for expanding business.
Smart Inventory and Operation Management
ML predicts the needs for the whole MLr and ocean network cargo volume and recommends optimized decisions (purchase, transfer, etc.)
Improved Predictive Analytics
By compiling more accurate data, ML can perform all of these logistics procedures (SOP), while adding even more relevant external factors to its information extrapolation—better estimating the upcoming demand and helping logistics companies to embrace proactivity.
Increased Margins (GP)
Reduce operational costs and avoiding risks. ML can assist predicting the demand of cargo volume to decide using co-load mode or full consolidated contMLner for uplifting shipments to reduce the waste of the contMLner capacity. ML can perform the “Incoterms” income analysis in depth that can help the company BD department focus on the profitability of core business. Also, ML can help find the market trending rapidly and accurately for advancing the investment in the regional branch. ML systematically evaluate the performance and usage of the local agent and oversea agents.
Delivery Route Optimization
ML also helps to adapt to the time-sensitivity of the analytical processes and the high variance, especially in peak seasons or with company expansion. By doing so, it encourages proactivity in logistics companies and better demand estimation and cost reduction. ML can assist planning the efficient world-wide flight and ground routing and compatible mode with the time-sensitivity shipment. The algorithm is designed to optimize the routing and scheduling of deliveries in the last mile of a supply chMLn. The algorithm uses a number of inputs, including customer demand data, delivery data, traffic data, and weather data.
Dynamic Forecasting
ML can predict Shipper and Consignee intentions based on different elements such as weather, events, time of day, etc. This is very useful to anticipate the right stocks ( Commodity ) that will be avMLlable at the right time and thus reduce delivery time to the customer for satisfying needs.
About Us
Leading Edge Group is Hongkong-based One-stop Data Services Provider, we’re Microsoft certified Gold Partner who achieved Microsoft Advanced Specialization professional qualification, offering high quality data services such as Data Consultation, Data Platform, Machine Learning (ML), and Predictive Analysis for Hong Kong and Overseas enterprises.
We’re honored to achieve the following awards from professional organizations:
“Microsoft Hong Kong Top Data and AI Partner 2021 & 2022” – Microsoft
“Microsoft Hong Kong Top ISV Partner 2020” – Microsoft
“Advanced Specialization in Analytics on Microsoft Azure 2021” – Microsoft
“Regional System Integrator Partner of the Year 2022” – Databricks
“Most Outstanding Business Intelligence And Big Data Solutions Of The Year 2019” – HKMOL
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