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causaLens launches the first causal AI platform

The revolutionary enterprise platform provides businesses explainable and actionable insights by understanding cause and effect.

The release of the platform was covered by Hedgeweek, Startups Magazine and Institutional Asset Manager among others.

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LONDON–(BUSINESS WIRE)–causaLens, a deep-tech company predicting and optimising the global economy, has released the World’s first causal Artificial Intelligence (causal AI) enterprise platform. Businesses no longer have to rely on curve-fitting machine learning platforms unable to handle the complexity of today’s world. They are invited to join the real AI revolution with a platform that understands cause and effect.

“Our platform takes a radically different approach. Causal AI teaches machines to understand cause and effect, a necessary step to developing true AI. This allows our platform to autonomously operate at a new level of abstraction that explains to businesses what actions they need to take to achieve their objectives.”

The causaLens platform defines a new category of machine intelligence. Its next generation AI engine harnesses an understanding of cause and effect relationships to directly optimise business KPIs.

“Businesses investing in the current form of machine learning (ML), including AutoML, have just been paying to automate a process that fits curves to data without an understanding of the real world. They are effectively driving forward by looking in the rear-view mirror,” explains causaLens CEO Darko Matovski. “Our platform takes a radically different approach. Causal AI teaches machines to understand cause and effect, a necessary step to developing true AI. This allows our platform to autonomously operate at a new level of abstraction that explains to businesses what actions they need to take to achieve their objectives.”

causaLens has a track record of breaking new ground, having pioneered automated machine learning (AutoML) for time series data. The causal AI platform retains the advantages of comprehensive automation, allowing thousands of data sets to be cleaned, sorted and monitored at the same time. However, it combines it with causal models and insights that are truly explainable – traditionally the sole province of domain experts. Unique human knowledge is harnessed through intuitive interfaces for human-machine partnerships.

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