Our Innovation Analysts recently looked into emerging technologies and up-and-coming startups in the logistics industry. As there is a large number of startups working on a wide variety of solutions, we decided to share some of our insights with you. This time, we are taking a look at five promising machine learning solutions impacting last-mile delivery.
Heat Map: 5 Out Of 100 Machine Learning Startups
For our 5 picks of machine learning startups in this category, we used a data-driven startup scouting approach to identify the most relevant solutions globally. The Heat Map below highlights these five interesting examples out of 100 relevant machine learning solutions, specifically used in last-mile delivery. Depending on your specific needs, your top picks might look entirely different.
Detrack – Geocoding Artificial Intelligence (AI)
Last-mile delivery is about optimizing time and itinerary for the final step of the supply chain. With the help of AI, algorithms collect and analyze the mapping and geolocation to provide the most efficient, convenient, and the quickest way for transport. For example, Detrack offers a geocoding AI called George. This service provides accurate optimization of the road without any geographical limit. The system learns and improves thereby enabling a self-correcting process without the need for human interaction.
Freightos – Anticipatory Logistics
Understanding the customer is a significant part of logistics. With the help of the gathered data from purchases, deliveries, customers’ questions, frequency of orders, and other details eCommerce platforms offering last-mile delivery as a service can fully analyze this information. Another direction of the anticipatory logistics is actually anticipating the next purchases before an order is made. US-based startup Freightos, for instance, offers an analytics solution which shows how to minimize future expenses by analyzing past expense rates.
ClearMetal – Accurate Timing Metrics
Information regarding the delivery time, cancelation, and new orders change very quickly within short periods. This raises the problem of accurate self-updated information for the stakeholders. However, the integration of AI within last-mile delivery systems make it possible to view the updated information quickly. US startup ClearMetal provides real-time visibility of the last delivery process and anticipates the delivery due time as well as updates tracking details.
Robby Technologies – Navigation And Interaction
One of the common difficulties for last-time delivery is reaching the final destination, i.e. getting through the narrow streets which not every car can drive through. With the help of maneuverable robotics, it is now possible to reach the final point through pathways. Such robotics learn how to drive through narrow pathways, improve navigation, and interaction with people. For example, Robby Technologies enable their robots to apologize when they unexpectedly block the way for a person. Their robots memorize the road, they avoid obstacles easier, detect humans quicker, and finally optimize the last-mile delivery process.
Package.AI – Voice Recognition
Time optimization can be achieved with the help of Natural Language Programming (NLP). Last-mile delivery systems which work on the basis of voice recognition make it easier to change the time, road, and other details regarding the delivery without the need to pick up the phone or go online. Israeli startup Package.AI develops the chatbot Jenny for different types of assistance during the last-mile delivery process, including changing the time of the delivery, editing details, canceling the order, talking to the recipients via social networks, etc.
What About The Other 95 Solutions?
While we believe data is key to creating insights it can be easy to be overwhelmed by it. Our ambition is to create a comprehensive overview and provide actionable innovation intelligence for your Proof of Concept (PoC), partnership, or investment targets. The 5 machine learning startups showcased above are promising examples out of 100 we analyzed for this article. To identify the most relevant solutions based on your specific criteria and collaboration strategy, get in touch.