An ERP System For the Cannabis-Based Products Distributors

SPsoft has had to deliver a technology solution that would resolve a financial issue of inefficient resource management and planning. Thus, the accounting systems’ data has had to be synchronized and transferred into the unified platform, while preserving the accounting systems’ individual functionality. Furthermore, the platform required a myriad of solutions needed for tracking, managing, and controlling the commodities within the marketplace.

SPsoft has managed to meet the customer’s requirements comprehensively by creating a platform that has become a unified supply chain management tool for medical cannabis distributors. The properly divided by our Python Architect source artifacts have catered to the establishment of viable business logic, which now lets our partner’s customers plan and manage their supply chain efficiently. The speed of solution delivery combined with the experience required took our customer’s product to market sooner, thus saving him a lot of money. The ongoing inclusion of ETL, DevOps, and QA specialists into the project has extended the scope of our performance, letting us deliver a flawless solution that met our client’s business needs to the full.

Our client was looking for a reliable tech partner to provide a Python Solution Architect Team Lead to initiate the platform’s development and take charge of it in the long run. Regardless of a pressing deadline, we have provided the expert who has eventually taken to work after only one week of onboarding. 

Our cooperation started on 1 October, and the system’s preliminary structure, approved by the customer’s technical expert, was ready by November. Having harnessed Python, Django, Sage Intacct, and Intuit QuickBooks, we created a cloud infrastructure providing each distributor with customizable supply chain management and accounting solutions. The platform’s cloud infrastructure has been audited and gauged in accordance with the latest “high-efficiency” recommendations provided by Google, as we kept on extending the team, adding Python DevOps, ETL, and QA specialists to it. 

The beginning of December marked the delivery of an already working system capable of synchronizing and processing the data required. Following the platform’s testing and optimization by our joint QA team, we came up with advanced testing requirements for the ongoing support of the platform, extending our team with a QA responsible for strengthening our partner’s QA approaches and practices.