TrendPlus provides AI/ML advice and proof of concept implementation for your internet-based business.
We provide advice and solutions in the form of detailed guidelines and a sketch of implementation based on the requirements of your business to improve efficiency, reduce operational costs, and remove pain points. We can go even one step further, by implementing our proposed solution as a stand-alone software service that can be easily integrated into your current system.
TrendPlus is known for its superior service using cutting-edge technologies such as AI/ML, optimization tools and algorithms, edge/cloud, and agile-based software development methodologies to fulfill customer needs as well as agile reaction to requirement changes with respect and confidence. TrendPlus has a team of experts with Ph.D. in computer science, data science, computer hardware, embedded systems, and applied mathematics, as the key competencies required to deliver its services.
Based on your interest, we can set up an online/on-site meeting with you free of charge to discuss your business plans and objectives to analyze and identify your challenges and pain points, and how they can be relieved by using our suggestions and solutions.
TrendPlus Service Workflow
Projects we Involved
Real time Scheduling Project
In this project, a real-time job scheduler for 5G-RAN in a Base-Band Unit (BBU) was developed in the form of a PoC (Proof of Concept) for a hierarchical inter-cluster and intra-cluster scheduling to not only efficiently schedules all tasks but also considers load balancing, dependencies, timing and other system requirements. We started with identifying the parameters, formulating the problem, then proposing state-of-the-art algorithms to deal with the optimization problem, and finally analyzing the result.
Routing Optimization Project
In this project, we developed an optimization software service for solving a Constrained Vehicle Routing Problem with Time Windows (CVRPTW) based on VROOM in Python and C++. Multiple ML and Neural Networks models are also applied to predict the key parameters such as service time and vehicle capacities. CVRPTW is a keystone problem in (multi) hub-based last-mile deliveries to dispatch tons of items with the minimum cost in a timely fashion. A simple demo of the service is available in DockerHub.
Food delivery Project
In this project, an AI-based optimization software service to solve a Travelling Salesman Problem with Time Windows (TSPTW) was developed based on Google OR-Tools in Python. We also developed multiple ML-based features to predict the key parameters, including preparation time and service time. The goal of our optimization service is (1) to maximize end-users satisfaction by delivering food in the expected time and (2) at a minimum cost per delivery while respecting the constraints. A simple demo of the service is available in DockerHub.