CLIENTLeaveTown, a Canadian company operating in the travel industry GOALLeaveTown Enriching the client’s property listing by creating a solution that handles different kinds of integration flows exposed by individual providers in real-time? Challenge Accepted! WE MADE IT! Our client was looking for a way to enrich their property listing. A solution was needed to aggregate and synchronize offers from a variety of third-party property providers within the client’s existing system, including criteria such as booking status and pricing. Our team was tasked with designing and implementing components which allow efficient integrations between the core of the system and the external property providers. The second step was to integrate a few external providers. Because integration possibilities differ in many ways from provider to provider, getting offers and keeping them in sync requires implementing various push/pull mechanisms, real-time notifications, or a mix of both. Such services involve a variety of technologies like FTP, WCF services, and REST APIs, as well as providing data in different formats like text, XML, JSON, and more. For these reasons, particular integrations were implemented independently as separate services with dedicated databases. All data exchanged between them and the core component of the system was handled by the middleware component. Creating such a message broker ensured compatibility with the core of the system, while simultaneously providing a lightweight interface for the new integration services. TOOLS Azure, #C, .Net, MSSQLCheck out more: https://nexocode.com/case-studies/aggregating-offers-from-a-variety-of-p…

CLIENTPharmaceutical SectorGOALRunning AI Design Sprint workshops focused on discovering opportunities for applying machine learning solutions in the pharmacovigilance sector? Challenge Accepted!WE MADE IT!The client is a pharmaceutical company that operates in the pharmacovigilance sector. They were looking for opportunities to apply machine learning solutions in their PV workflows. However, they lacked expertise in this area and didn’t know where to start.We ran AI Design Sprint workshops with the client’s PV team to help them discover opportunities for applying machine learning solutions. The goal was to map the current PV workflow and identify potential pain points that could be addressed with machine learning solutions.The first step was to understand the client’s business context and objectives. We then gathered data about the PV workflow from various sources, including interviews with PV experts, a review of existing literature, and an analysis of publicly available data sets.Next, we used this data to generate insights about potential areas where machine learning and natural language processing could be applied in the PV workflow. Finally, we created a prototype solution that demonstrated how these machine learning solutions could be integrated into the PV workflow.TOOLSPython, Natural Language Processing, TensorFlow, Google Cloud Platform, AI Design Sprint If you’re interested in learning more about AI Design Sprints and how they can be used to solve problems in your organization, contact us today! We’d be happy to chat with you about your specific needs and objectives.

CLIENTTravel SectorGOALDeveloping a platform that enables smooth corporate travel booking and management? Challenge Accepted! WE MADE IT!The client, a large travel management company, approached us with a challenge to develop a corporate booking tool that would make business travel easier and more efficient for companies of all sizes.The solution we provided was a web application focusing on business trips. It included all the features our client required, such as an extensive range of travel options, management tools, and 24/7 support.We developed multiple integrations with various flight providers, accommodation engines, and integration with rail providers to provide a large travel inventory. Thanks to direct integrations with providers, the platform offered special prices compared to other solutions.We delivered management features, including an approval process, booking delegation, and spending limits. The tool had advanced options for user management and setting and executing travel policies. Additionally, we built a recommender system that provided travelers with personalized recommendations based on their previous bookings. This way, they could easily find the best travel options for their needs without spending hours searching.Lastly, to provide a smooth expense management module, we developed an NLP-based feature that enables photo uploads of all travel invoices and automatically extracts all the relevant information such as cost, date, and vendor. This way, employees can easily submit their expenses for reimbursement without having to fill out tedious forms.Thanks to our efforts, our client now has a platform that can offer their corporate clients a wide range of travel services that are easy to use and scalable. The user-friendly platform design and custom illustration make corporate travel booking and management smooth and pleasant. TOOLSJava, Vue.JS, Python, Tensorflow, Google Cloud Platform