Predict outcomes where speed and accuracy matter
Physics-Informed Predictive AI combines scientific inputs with AI to accelerate projects with complex interconnected data. Use it to overcome the strong limitations and inaccuracies associated with conventional AI and Machine Learning (ML). We deliver accuracy in an easy-to-understand format.
Disparate data, not enough data?
Our science team guarantees meaningful insights within 8 - weeks, overcoming limitations of narrower and disparate datasets that add to project complexity.
International award-winning science, patented technology, and recognised leadership
Our clients have access to an award-winning science team with awards and technology, including; Alfred P. Sloan Foundation Research Fellowship, Breakthrough Prize, Gruber Prize, Einstein Medal, and the Bruno Rossi Prize.
Our company is a member of the NSW Government Data and AI Taskforce (Australia), supporting strategy and future thinking. We are also incorporated in the USA and operate worldwide.
About NSW Government
The NSW Government has approximately 500,000 employees and has introduced world’s first initiatives including digital driver license now being replicated by the UK and USA. More
Fun Facts
As Australians, we like to think we have given the world some great inventions and innovations.
Soggy bank notes? Australian polymer technology are used around the world, important for our beach culture, peel it from your budgie smugglers (also Australian, sorry) and buy an ice-cream.
Let’s not forget the Australian CSIRO invention of Wi-Fi.
Corked wine? Research how Australia changed drinking habits globally with the screw cap, yes it makes us smile too, and why didn’t anyone else do this before us?
The wine cask, the Hills Hoist…..ok you get the picture.
Accurate Predictions
KartaSoft supports methodology known as Physics-Informed AI.
It is a progressive science using physics, biology and chemistry, and is applicable to critical infrastructure sector challenges where there is poor quality unstructured data & rare failure events that render traditional AI solutions ineffective.
The framework builds on and adds value to existing data science project efforts and targets the specific challenges faced by critical infrastructure.
Scientific evidence that proves robust strategies for:
• Validating regulatory strategies,
• Extending asset lifecycles,
• Predicting risk affecting customer experiences, and
• Optimising workflows.
Physics Informed AI performs substantially where there is;
- a requirement for a higher level of predictive accuracy, limited data, and rarity of failures that make conventional ML and AI approaches inadequate,
- a need to overcome inaccuracies and strong limitations of a yes/no analysis framework,
- a need for greater diagnostic capacity,
- a requirement for accurate predictions of physical process causing failures, and
- a need to overcome limitations of narrower datasets, where spatial correlation is physically inaccurate.
Customer Quote from a major water utility
‘Over the last ten years we have partnered with a leading university, funding much of their research. Their models were found to be very accurate across a very small subsets of data. However, when this model was applied across data from our $43bn network its prediction accuracy fell to below 10%. Imagine reading a document where only one word in ten makes sense! Now overlay the costs associated with poor predictive accuracy.
In contrast, KartaSoft Physics-Informed AI quickly identified the parameters causing failures. This is the most important element of any risk mitigation strategy. Once this was demonstrated and properly understood risk mitigation strategies were supported with confidence’. Senior Manager, Australian Water Utility.
Mathematical Framework
The KartaSoft framework is not revolutionary and uses base sciences. The methodology has undergone extensive market testing, and a robust peer review process in Florida during the patent application process. This confidential unbiased point-of-view from Professor Dr Imre Bartos and Dr Ian Oppermann will deliver valuable information for you and your executive team, in an easy-to-understand format. We are confident that it will add to your thinking, and how planning and forecasting is viewed over the coming years.
Physics Informed AI performs substantially where there is;
- a requirement for a higher level of predictive accuracy, limited data, and rarity of failures that make conventional ML and AI approaches inadequate,
- a need to overcome inaccuracies and strong limitations of a yes/no analysis framework,
- a need for greater diagnostic capacity,
- a requirement for accurate predictions of physical process causing failures, and
- a need to overcome limitations of narrower datasets, where spatial correlation is physically inaccurate.
Customer Quote from a major water utility
‘Over the last ten years we have partnered with a leading university, funding much of their research. Their models were found to be very accurate across a very small subsets of data. However, when this model was applied across data from our $43bn network its prediction accuracy fell to below 10%. Imagine reading a document where only one word in ten makes sense! Now overlay the costs associated with poor predictive accuracy.
In contrast, KartaSoft Physics-Informed AI quickly identified the parameters causing failures. This is the most important element of any risk mitigation strategy. Once this was demonstrated and properly understood risk mitigation strategies were supported with confidence’. Senior Manager, Australian Water Utility.