Gravelsoft

As I mentioned earlier, our company started approaching the Banking segment of potential clients, and there was a clear need to extend our monitoring module for banking-type-of-environments. We defined the exact scope of development together with Anna (BA from Gravel), and after three weeks, the scope was split into three milestones and put to Trello. Overall from their side, they were allocated 3-5 engineers depending on the project phase, and I was leading their work every week. The leading tech we use is Python, including AWS S2 and GCP AI. There was bash scripting for autoscaling scripts. Guys developed a full extension of our platform from Gravelsoft.

We are a software company which provides intelligent commerce for B2B companies. We were looking for a nearshore company that can help us to build MVP for our core calculation engine, which is able to process the sale-historical data and provide the demand forecasting based on few scenarios. This MVP was intended to engage new enterprise customers this year. The whole MVP was estimated in a range of 5-6 months which aligned with my expectations. In due course of the development, Gravelsoft has delivered three major releases every two months. First, they produced an ETL layer to onboard customer’s data and transformed it in a way that algorithms can use it. Then we released an AI/ML part that actually is able to process the historical and sales-related data and build the demand forecasting. Eventually, we released the API that wraps up while logic and is ready to use by end customers. We were impressed that they have had in-house ML and ETL building expertise as well as guys who were not afraid to commit to delivering solutions. Their engineers have outstanding skills, and they are class A engineers for such tech complex projects.