AI Based Assistant App For A Music Industry Giant

The client, who was looking for Flutter developers, approached us after hearing about our extensive work in the field of app development using machine learning. The idea behind the collaboration was to provide a digital solution in the form of a single app that could provide AI based services for various verticals, utilising both touch and voice UI, hence making the entire process orderly. It was crucial to ensure that the application had the required privacy settings considering it would deal with personal data from the users. An AI proprietary engine was also to be designed which would enhance the UI, hence providing users with an enhanced experience.The engagement model that was chosen for this project was the T&M model using scrum methodology as it provided flexibility which was integral for an extensive project of the sort. We initially held multiple discussions with both the scrum team and the client using Azure to track development, and came up with a plan to hold 2 week sprints which would be planned and executed accordingly.

As with any project of this scale, the venture came with its own set of challenges. One of the first challenges our team ran into was realising that some of the gestures portrayed on the screen were too complex for users to understand, so we had to implement tutorials as a fix to this. Some of the other issues that the developers ran into were realising some of the screens were functioning at a slow rate and any plugins were failing the security standard and it was crucial to identify and address each issue individually. The team also used Analytics extensively to understand the user's behavior as this would define the way some of the features were to be implemented. Some of the features requested by the client could not be designed using the existing packages; our developers had to conduct research and experiment in order to make these changes as some of the packages had to be built from scratch. As the project progressed along the course, the app was growing in parallel due to which it was becoming increasingly difficult to detect bugs. We implemented dashboards and crash analytics to make this enhance this process. As there were many developers working on the same app, we had to bring about significant changes to the architecture in order to clearly define boundaries and streamline the application. 
In bird's eye viewThe engagement model chosen to interact with the client was the scrum methodology using Azure to track development progress.Amazon S3 was finalised as the desired cloud storage platform for the project along with Zipkin to detect any latency errors.The development team conducted extensive quality assurance checks using Appium and Selenium.

The project is currently in progress, with our development team currently working on the 37th sprint. Features are constantly being put through rigorous tests and enhanced, with new releases coming up every week. The client is ecstatic with the progress of the platform which is currently in its Beta stage and has commended the team for their excellent crisis management skills and the technical expertise shown along the run. It has been a pleasure being a part of this endeavour with our partner on their goal to revolutionise the way life is lived using cutting edge machine learning techniques.