We are different from the competitors for some reasons:
Firstly, we have an impressive client portfolio including customers are the top 10 biggest corporations nationwide and globally. This gives us a strong push for market penetration.
Secondly, Abivin offers businesses the best price over benefits in the SEA market (and even globally) with persuasive ROI.
Thirdly, we provide great local support for customers based in ASEAN, with automatic translation and localization for app and user guides. Plus, flexible features, customizations are available based on customers' requests.
But above all, technology is the biggest factor that differentiates us from competitors.
Developing optimization algorithms is not an easy task. To develop optimization algorithms, you not only need normal data scientists, computer scientists, or computer engineers. You need mathematicians. Our Abivin team consists of multiple champions of international informatics and mathematics competitions, as well as machine learning engineers and computer scientists with years of experience. With such a robust team, we are confident to solve the most difficult logistics problems, satisfying constraints that our competitors can not address effectively.
Our technical capabilities also allow us not only to solve problems effectively but also to prioritize solving the most difficult problems. We successfully solved the Vehicle Routing Problems, 3D Loading, Pickup and Delivery Problems, and Carriers Selection. These logistics problems are not new, but since technologies like the internet, cloud, or mobile have developed, the above problems have become more and more complex in terms of practical execution. By leveraging a team with strong technical capabilities, along with a huge cost advantage compared to other competitors, we have successfully brought high saving values to the biggest corporations in each segment. Moving forward, we will apply our technology to smaller companies to achieve sustainable growth.
Finally, once we gather enough data from different types of delivery models, the next step is to perform machine learning. In each segment, there are 1-3 biggest companies that hold ~80% market share. By having those companies as our customers, we have gathered enough data to stay far ahead of the competition. Our algorithms will utilize the data, learn from historical route plans, and produce more efficient routes in the future. For example, we can learn how to best cluster the delivery points in each area, so as to apply the same mechanism to other route plans.