Bringing an idea from a poc to production is one of the main challenges data scientists struggle with today. While there’s yet no consensus solution for this, recently more and more leading companies began building data science infrastructures. These are designed to support the cycle of research, deploy, retrain and monitor. My team at Check Point is currently focusing on building such infrastructure for company-wise use, while keeping in mind various use-cases, different data types and separate production environments. In this talk, I’ll share our work done in this area, and our future vision for this infrastructure, and how we tend to build it.