PyRISK™ is expected to save 60% of the work effort through the full utilization of Machine Learning. The outcome is a faster and better decision support and simpler and easier risk communication in all phases of an asset’s life cycle. We estimate that PyRISK™ can reduce the overall cost of safety studies by 40 to up to 60% over the lifetime of an asset, as it is based on dynamic risk estimation and decision making. PyRISK™ unlocks opportunities for machine learning in risk management. It supports customers already using PyRISK™ to perform Dynamic QRA to get even more value from the data at no additional cost. The PyRISK™ approach offers significant cost advantages. Our estimate is that an operator may end up spending 30–40% less on safety studies over the 25 to 30 year lifecycle of a medium to the large-sized asset, while getting much more value out of the data generated in their QRA studies.
Supply for libraries can take an enormous amount of time, and costs can be big as well. Every new book means more space needed for it. With our recommendation system, we can provide you with optimization of your costs and recommendations on how many books and from which sections you should buy based on your data.
PyHAZOP™ has the capability to depict the outcomes visually on the risk chart. This visualization tool empowers the users to come up with inescapable conclusions about the risk reduction measures. The best-suited approach we offer in PyHAZOP™ is the ability to quantitatively determine the degree of vulnerability based on dynamic modeling for the nodes (unit operation) in the assessment based on mathematical-based approach.
Some of our clients
Manja delivered extraordinary work and thinking outside box helped us to see how we can move forward in our projects.
It was great to work on several projects at the same time and to uncover the power of AI from my side and from Manja's side. A pleasure to work.
We are very satisfied with work with Optimize GS and Kagera. As we will continue to collaborate in the future.
Brought to you by Cambridge Spark, Data Science Specialists. Written by guest blogger, Manja Bogicevic. In just 10 minutes, 16 players with 6 balls can produce almost 13 million data points! The origins of football go way back from the beginning of the time, some...
Just over 20 years ago people didn’t even know what the internet was. Today we can’t even imagine our lives without it. Today I am going to give you a quick overview of what deep learning is and why it’s picking up right now. And the reason why we are going back to...
Machine learning is an extremely useful tool. You have public, but mostly they built behind the scenes. Machine learning is used to solve hard problems for different companies. How can I use ML to build smart and profitable tool from our data? — If you are asking...
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