The investment will accelerate the delivery of industrial-grade AI software
An artificial intelligence (AI) and cognitive computing company, Beyond Limits, has revealed that it has secured $20 million in Series B funding from BP Ventures, the corporate investment arm of global energy business, BP.
The delivery of industrial-grade AI software will be accelerated by the investment. The software was previously used in deep space investigation missions, to combine human knowledge with machine learning and provide the energy sector with new levels of operative insight, business optimization and process automation across all operations.
Beyond Limits, launched in 2012, is a leader in AI and cognitive computing. It will adapt and deliver AI software that tackles industrial and enterprise challenges here on earth, with technologies proven in the unknown and extreme environment of space.
Meghan Sharp, managing director BP Ventures - Americas, said; “BP Ventures is excited to help Beyond Limits grow into new verticals, as we bring forward the pioneering work they have developed with the space program to our industry and throughout our businesses. Our investment in Beyond Limits is an example of BP’s ongoing support of entrepreneurs and innovators not only inside the traditional world of fuel and natural gas but those looking toward a new energy future.”
A step change in the way BP locates and develops reservoirs, produces and refines crude fuel and markets and supplies refined products could be enabled by the BP - Beyond Limits partnership. The expertise of Beyond Limits could be brought to the world of fuel and natural gas whereby, using its AI software could support improvements in the speed and quality of decision making, manage operational risks, and harness the collective knowledge and experience of its team.
“Our goal is to create automated solutions that can think like humans and augment human capability,” said AJAbdallat, CEO of Beyond Limits.“We are the AI Company that provides solutions for problems that cannot be solved using traditional approaches.” PWKD12062017