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The global energy sector is at a turning point. Rising demand will outpace supply, and rising political, legislative and cultural pressures have made it harder to deliver efficient and safe production. New energy sources will not meet the shortfall, bringing further pressure to downstream environments. Now is the time to bring Industrial AI into production environments to deliver higher output, more efficiency, and less carbon intensity. Cloud-based approaches deliver high performing AI in software industries, but this data science approaches were not designed for the dynamic, real-world, unstructured data sets of the energy industry. The result is underperforming models, high computing costs, and unnecessary security risks for oil and gas companies. The energy industry requires solutions that deliver market leading predictive intelligence on-location, using all available data, without requiring data processing, and without spending millions of dollars on compute costs. This is the mission that’s driven the past 3 years of research and testing at Kashmir Intelligence and has resulted in an infrastructure layer built specifically for the energy industry, on-site, using 100% of data, with no need for data processing in a completely secure architecture at 1/10th of the cost and complexity of cloud and centralised approaches. Kashmir Intelligence exists to build better worlds through machine intelligence.

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Dan Jeavons is the President of Kashmir Intelligence.

3 people are employed at Kashmir Intelligence.

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