What is Pallium

Pallium is a platform where scientists, researchers, and stakeholders solve hard problems. Users with shared domain expertise to collaborate in building a graph of causality. Using these graphs, users can identify and work to disrupt a flow of events prior to terminating into an outcome.

Companies, scientific research communities, and other organizations will use Pallium to deconstruct complex and high-risk systems into networks of cause-effect events, visualized as directed graphs, in a collaborative environment. Networks can be kept private for internal collaboration (industry applications), or made public and monetized (non-profit organizations and collaborative science applications).

On AI and ML

ML algorithms that learn DAG structure do so by analyzing a single dataset that has all relevant data measured together, an approach only realistic in settings such as manufacturing and other well-controlled, process-oriented applications. Causal explanation in complex, uncontrolled, real-world domains requires the ability to integrate evidence and findings from many separate experiments conducted in a piecemeal fashion, asynchronously over a period of years, and with varying levels of quality. Insights garnered from a tool such as CausaLens might be considered to be but one piece of the broader causal puzzle that Pallium allows users to assemble.