Data must be treated at the right place and time
Andry RAZAFINJATOVO – CEO
“Data engineering is key to get value from your data science projects, We cannot wait until the end of the development phase to be sure of their ROI. We aim to allow our customers to reduce their time to market dealing with up to 100% of data engineering tasks from the execution to the maintenance of their data workflows.”
David GLESSER - CPO
“We created Ryax Data engineering platform to fill a gap between the Data Scientist and the production. Data Science is made of old and new algorithms, open source and proprietary tools and must be run on all kinds of IT infrastructure. Data Scientists must focus on what they are best at: defining algorithms. On our side, we must provide them a platform that they will be able to use directly to push these algorithms into production.”
Yiannis GEORGIOU - CTO
“Modern data and compute-intensive applications involving IoT, Big Data and Artificial Intelligence use cases drive data in such high volume, velocity, and variety that decisions and actions must be made quickly, or their value will evaporate. The Edge computing and hybrid Edge-Cloud paradigms will handle it but Data Engineering complexity will grow with it. We must help Data Scientists to be able to exploit these new infrastructures.”