Supporting better decisions
What can you expect from a KartaSoft solution?
How long is a project?
The initial pilot period is 8 weeks.
When can meaningful insights be expected?
On average expect meaningful insights from week five and finalised by week eight.
What customer internal resources need to be involved?
Extremely limited. We will do the heavy lifting, data acquisition, and know the questions to ask to expedite delivery. Weekly cadence meetings will be setup during the pilot period. This is important to ensure a cohesive team approach and provide clarity for both parties. Our model is fully supported to ensure that there are continued optimised insights that make sense to all stakeholders. Our objective is to support better decisions.
Who oversees the delivery?
The delivery is overseen by our award-winning science group. Customers will have direct access to the team, during the pilot and subsequent project delivery - ensuring continuous improvement.
Technology
The insights platform is delivered on AWS infrastructure. Scaling, load times and accessibility, are not an issue. As a customer, insights can be shared with designated third parties to add to their value chain.
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.

Solutions
Maximising operational value and reducing corporate risk by providing greater analysis predictability. Diagnostics for government and large enterprises.
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.

Co-innovation journey
Our methodology works where conventional monitoring methods fail. Providing powerful insights where human interpretation is difficult, there isn’t enough data, and failure events are rare.
Learn More
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.

Government
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.

Why work with us
We work with your team to achieve insights faster.
Our customers have access to our award-winning science team and patented methodology that always guarantees actionable insights.