Supporting complex projects with top-tier software development services.

Our client recognized that building a firm base of software engineering into the project would make it much more successful than trying to piece several smaller custom software product development projects together at the end. That is why we began by defining the support delivery processes. We took care to align those processes with the client’s end business goals. We recommended a ticket management tool, Jira Service Desk. We then helped configure and customize the client’s version of the service desk to help manage tickets raised against software issues. When issues were raised, the client and our team were able to address them quickly, tracking and recording successes and solutions.

Our award-winning software design service involved using natural language generation (NLG) to help the client’s survey writers generate false or incorrect answers to their survey questions. We built an app that used Terraform scripting to automatically generate responses to survey questions. Writers could then select from these options. If the writers chose an option, the program would learn that answer was acceptable. The writer could also generate more options, which would tell the program that the options didn’t work for the writer. The program would use this feedback to inform and improve future options. This constant learning and evolution means the program continued to increase the writers’ productivity. The auto-generated questions even increased the productivity of new writers, as they no longer had to rely on more experienced writers for training. This project was so successful, in fact, that the client asked us to discover new ways to integrate automation into other parts of their business.

Our client wanted to migrate to a new cloud-based database while we also automated content generation. We provided AWS cloud migration support that included software product development and enhancements using Java and Angular, with product support from Oracle PL/SQL. We also used Oracle for database administration. When we began migrating data, we built a testing suite using Manual, Selenium, and FitNesse that allowed us to validate selected test data during the migration. That way, we could verify that data could be migrated accurately, without the need to test every single file and piece of data. This sped up the process of migration significantly. The testing suite also highlighted failed files and generated reports in Excel and in the FitNesse wiki. That gave us the necessary clarity and allowed us to manage the quality of the data during the migration without slowing the whole process down.