causaLens, a deep-tech company predicting and optimising the global economy, has released the World’s first causal Artificial Intelligence (causal AI) enterprise platform. causaLens says its platform defines a new category of machine intelligence and that 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), eg 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,” says 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.
Since its inception in 2017, causaLens has worked with a range of corporates across multiple industries. Customers include some of the world’s largest Asset Managers, Hedge Funds, Tier-1 Investment Banks, Transportation and Logistics companies, and Energy and Commodity traders.
Masami Johnstone, Head of Information Services at CLS, whose products help clients navigate the changing Foreign Exchange marketplace, says: “The causaLens platform has enabled us to discover additional value in our data. Their causal AI technology autonomously finds valuable signals in huge datasets and has helped us to understand relationships between our data and other datasets.
“As a recent example, we were able to identify significant and unexpected changes in key factors associated with the FX markets during the Covid-19 pandemic. This has been immensely valuable to our clients, enabling them to quickly react to market conditions and enhance their investing strategies.”
Today’s world is changing faster than ever before. Current state of the art ML barely scratches the surface of what machines can do. Causal AI is the next huge step forward.