Science meets engineering
We have three teams (data engineering, devops and data science) with different academic background and different views on any solution we create. This gives us and our clients competitive advantage because we look at problems from different angles. The result is the best solution with the right set of tools running on an optimal infrastructure with pluggable ML and AI algorithms which are fueling business.
We work with the clients, not for the clients. If you have a problem we will solve it but we will try to understand your business and see how we can impact it with the best possible solution. We might recommend a thing or two along the way. Remember, we have seen a lot over the years.
Neither us nor our work is a black box to our clients. Our reporting practices will always keep you in the loop. We start off with a face-to-face workshop with a clear goal to create milestones and timelines. We leave TDR (team decision records) for every important architecture change, we provide weekly reports on our progress and we like to organize a demo to show you what we did and get early feedback. We strongly believe that this is the formula for a successful solution.
We invest in knowledge
Learning is exciting. It is one of company values we value the most. We have employee knowledge budget which can be spent on continuous improvement through courses, books, conferences, workshops. We also contribute to the community by sharing our home-grown tools as OSS Projects on GitHub, lecturing at conferences world-wide, organizing local Big Data Meetup each month and active writing of blog posts. All these factors make us better professionals and the quality of your next project will be better if you decide to work with us.