{"id":26271,"date":"2020-07-24T09:55:57","date_gmt":"2020-07-24T07:55:57","guid":{"rendered":"https:\/\/www.intellias.com\/?p=26271"},"modified":"2024-04-26T12:42:17","modified_gmt":"2024-04-26T10:42:17","slug":"automated-onboarding-for-an-uber-for-trucking-app","status":"publish","type":"post","link":"https:\/\/intellias.com\/automated-onboarding-for-an-uber-for-trucking-app\/","title":{"rendered":"Automated Onboarding to an Uber for Trucking App"},"content":{"rendered":"
Our client is the provider of a real-time freight marketplace that logistics and transportation companies use to move over 1.3 million shipments around the world each year. This marketplace connects shippers \u2014 usually big logistics companies and retailers who need subcontractors for freight transportation \u2014 with drivers or smaller transportation companies in search of orders.<\/p>\n
The marketplace essentially works like an Uber for trucking application. The app enables couriers to place orders for shipments and allows drivers and small transportation companies to fulfill them.<\/p>\n
To assure couriers that their products are in good hands, Uber for trucking companies have to establish baseline criteria for drivers, vehicles, and transportation history. Only after comparing a new driver against baseline criteria, an Uber for trucking app allows the driver to apply. Initially, our client\u2019s support center manually checked all drivers\u2019 and companies\u2019 documents for compliance, which made the onboarding process last for months.<\/p>\n
Our client needed to more effectively onboard new businesses and drivers into their freight management marketplace as well as optimize the time and resources spent on the onboarding process. To do that, they searched for a software development partner with expertise in the logistics and transportation industry <\/a> to cover end-to-end component development<\/a> and propose an optimal solution for automating the onboarding process by applying advanced technologies.<\/p>\n <\/p>\n Our client entrusted us to develop a complete product ready for delivery to the market that organizes the process of onboarding new businesses into their freight management platform. Together with our client, we organized a series of workshops to decide on the optimal tech stack to cover the project\u2019s requirements. As a result of close collaboration with the product owner and our client\u2019s in-house engineering team, we came up with basic use cases to include in the onboarding process.<\/p>\n The freight management system assigns roles to different users, providing access to role-relevant functionality and organizing optimal onboarding. The basic onboarding scenarios include validating an individual driver with a vehicle and validating a transportation company with a pool of drivers available for delivery orders.<\/p>\n Depending on the user\u2019s role, onboarding may require a different set of documents to open access to relevant functionality. To ensure the most efficient experience for each user of an Uber for trucking app and minimize the involvement of customer support, we focused on automating features to eliminate manual work related to gathering data on new users and validating their documents.<\/p>\n We implemented a new component that automates data aggregation, processing, and decision-making through robust API integrations. This component automatically validates drivers, companies, licenses, vehicle conditions, and insurance plans, eliminating potential fraud.<\/p>\n Users upload documents to our client\u2019s system via an online survey. The system then parses user data to recognize identity of applicant, and the expiry date of the documents. Users also need to take real-time photos that the system then compares against their ID photos using image recognition software based on computer vision and AI that\u2019s specifically trained and optimized for documents and photo processing.<\/p>\n After successful onboarding into our client\u2019s Uber for trucking app, users can access a dashboard with all orders. In this dashboard, drivers can choose the most convenient orders to deliver. After a driver chooses an order, the system compares the driver\u2019s profile with baseline criteria. If the user is a match for the job, they\u2019re provided with all the data on the order including the address, customer, product provider, and receiver. Using the Uber for trucking, fleet managers can track orders and send instant messages to drivers to change delivery routes or provide shipment details. Uber for trucking works in mobile applications that help organize a driver\u2019s work on the go, including by synchronizing with navigation systems, while the desktop app is a convenient method for dispatchers to support drivers and manage corporate accounts.<\/p>\n The money and time spent onboarding employees, users, and assets is a burden on big companies. After successfully delivering an automated onboarding system for their freight marketplace, our client is planning to make this component marketable to sell it to other logistics businesses. Our client is paying special attention to data privacy and the security of data collected on drivers\u2019 and companies\u2019 profiles. Security measures they\u2019re taking include mitigating long-term risks, complying with international regulations, and conducting security audits.<\/p>\n To achieve better scalability and efficiency of their solutions, our client plans to extend their engagement with Intellias in an effort to substitute their monolithic platform with a microservices architecture. We\u2019ve already established an initial R&D team to work on technology stacks to migrate our client\u2019s platform to microservices.<\/p>\n Our client\u2019s automated onboarding system has cut the time spent onboarding new users from months to minutes. It eliminates the need to involve the support center to check all documents, saving money for our client, and allows users to start delivering products right away.<\/p>\n Our client continues to grow their business thanks to the introduction of new technologies and expects their revenue increase as a result of these changes to jump from the current 25% to 40% in the near future. While keeping their strategic focus on the UK market, they\u2019re now planning to expand their Uber for trucking app\u2019s reach into continental Europe.<\/p>\n","protected":false},"excerpt":{"rendered":" We\u2019ve accelerated the onboarding of new drivers to an Uber for trucking app by automating document processing and image recognition <\/p>\n","protected":false},"author":17,"featured_media":50276,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[5],"tags":[29,910,906,458],"class_list":["post-26271","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-case-study","tag-machine-learning-ai","tag-mobility","tag-transport-management","tag-transportation","technologies-angular","technologies-aws","technologies-bpmn-modeler","technologies-camunda","technologies-docker","technologies-java","technologies-jenkins","technologies-key-cloak","technologies-rest-api"],"acf":[],"yoast_head":"\nSolution delivered<\/h2>\n
User roles defined for onboarding workflows:<\/h3>\n
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APIs for automated onboarding to an Uber for trucking app:<\/h3>\n
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Business outcome<\/h2>\n