Our team encourages partnerships based on Agile Sprint Process.

It is a method of collaboration that makes the best accountability and flexibility possible by dividing a development process into periodic iterations called sprints. With constant client collaboration and feedback loops on every development sprint, we have a workflow that is far more efficient than any other.

A sprint is the most basic unit of a release, where we specify tasks: estimate, implement, test, deploy, and review them. During a sprint, ideally, no changes to the tasks or their ordering are allowed. Therefore, the shorter the sprint, the more agile we can be: ie we can make quicker decisions to do something different in light of knowledge we’ve acquired along the way.

As we break down the project into smaller iterations – sprints, we can have more precise point estimates and can also implement and execute the project in a way that the client team can be more involved. Both sides are always aware of the project status and deliverables. As a result we have a working prototype for you to use and interact with at the end of each sprint.

Complex problems often require complex solutions – such as Artificial Neural Networks and other Machine Learning algorithms. We have a plethora of experience in this area that ranges from fitting a tiny neural network on a smartwatch app, to building a core Machine Learning system for an Artificial Intelligence startup with more than 1 million users.

We are keen on setting up project infrastructure in the cloud even when the project needs to run on clients’ hardware. If applicable, we happily set up containerized services to be hardware agnostic and easily scalable.