The machine-learning platform for optimising pricing in brick-and-mortar stores
PostgreSQL
Python
JavaScript
Panther Pricing came to us because they were facing three significant challenges:
Panther Pricing was looking for a trusted tech partner with specific technological knowledge willing to support their internal development team. They didn’t have time for the lengthy onboarding process and needed results quickly.
Panther project has no middle management. Flat structure enables us to take the responsibility, make confident decisions, and contribute to the client's product development.
We wanted to ensure we had a complete understanding of the client’s problems to propose the best possible solution. That’s why we’ve started by negotiating the scope of the project.
The client agreed that writing the new front-end from scratch and integrating it with the existing backend solution would yield the best results within their budget and timeframe. We decided that FastAPI would be the right technology for the job.
We designed the new front end consisting of several reusable components. Such a design allows the client to use them as building blocks for their application's new features and functionalities, keeping the look familiar to the clients.
The client needed to improve our overall system performance and enable for continuous scalability. He was looking for external technology expertise in some specific development areas. Client also needed to act quickly and he was lacking the required additional development resources internally.
Bravelab proposed to migrate from the old technology (Flask) to the new FastAPI and refactor the current functionality. The goal was to optimise and reduce the technical debt of the application. We also adapted to the new front and accelerated the application.The solution is based on the latest front-end technologies.
Small and medium shops are facing intense competition in the market. The post-pandemic era has caused all retail industries to have the need to use online tools with automatisation systems to compete and survive.
Work with data in real-time has become one of the essential solutions for every company to make better choices. This time, Bravelab comes again with a cutting-edge strategy for Panther Pricing to solve this concept and provide a reliable result for all his clients in Germany.
Panther Pricing is a German company founded in 2018 and based in Frankfurt dedicated to providing innovative online services to boost retailers in Germany.
The plan was to craft a cloud software able to generate automated price recommendations for retailers in Germany. The mission was to allow bricks-and-mortar companies to have no more online sales with negative margin contributions. The platform should generate online benchmark prices for the clients.
At Bravelab we focus on creating a transparent process where communication between the client and our team is fluid and effective. We fully immerse ourselves in each project, so we can have a comprehensive understanding of the scope and establish the main objectives of the project:
Project Panther was focused on designing a collection of reusable components, guided by clear standards. Thanks to that solution, we can assemble and build any number of applications inside the platform, as well as keep consistency in the entire platform. The product is more than just a pile of reusable UI elements. It has structure and meaning. It’s not a generic web page, it is the embodiment of a system of concepts for sensible usage.
Thanks to the full integration of different stages and development stages we have created a powerful platform with the ability to automate 100% price recommendations in real-time using AI. With the Panther Pricing platform, our client helps retailers significantly improve their profit margins and revenues (gross margin increase of up to 5% points of revenues). A perfect integration from research, design, and development brought a platform with the following features:
In addition to AI-based sales forecasts, price elasticities, and online competitive pricing, item performance, current inventory levels, lifecycle, and order availability are all equally taken into account.
Our software house develops complex and sophisticated solutions for a wide range of markets and industries. From e-commerce to platforms integrated with AI and multiple integrations.
The team consisted of three an experienced and highly motivated developers, we had frontend and backend developers, and we were working closely with UI/UX designers.