SAPIAT’s tools and solutions are driven by our philosophy that unbiased, systematic decision-making is core to improving investment performance, and that it is important to consistently synthesize a broad array of sometimes inconsistent information sources, from market-derived covariance matrices to soft forecasts from independent research.


With over $100 trillion globally managed by asset owners, asset managers, and other institutions, the stakes are high for getting investment decisions right.

Looking at the complexities behind changing market regimes, geopolitical risks, secular and non secular changes, and climate change, it is now clear investors need more robust frameworks to explore the impact of uncertainty across different horizons, asset classes, and market scenarios.

Moreover such tools should provide not just mind-numbing numbers in flat presentations— but rather dynamic, interactive, powerful visualizations of the market environment and the impact of investment decisions.

To solve such problems, SAPIAT leverages machine learning methodologies, traditional and alternative data and high performance computing (HPC) –  uniquely combined into a single platform that is designed for investment decisions.


Traditional quantitative models implement powerful statistical methods, but often rely on linear approaches applied almost exclusively to market returns.  Approaches such as factor modeling are an essential part of the investment toolkit, but can be fragile to nonlinearities, stress conditions, and long tails.

Markets are not the only source of insight.  There are plenty of signals embedded in alternative data sources such as high frequency macroeconomic data, news, and in independent research.  However, noise is rampant in these sources also.  Information tends to be provided in heterogeneous formats – structured and unstructured – at different frequencies, with varying degrees of precision and horizons.  Synthesizing this information and converting it into actionable “investment intelligence” is at the heart of Sapiat’s mission.

Recent improvements in High Performance Computing (HPC) and large and non-traditional datasets – coupled with the judicious use of machine learning as well as traditional techniques,  enable SAPIAT to provide more efficient and robust insights to asset allocation, portfolio construction and manager evaluation.


Imagine a world where you are able to see the market ahead in the same way you would a weather forecast; where you are able to consume forecast information from a multitude of internal and external sources and build a “map” of the possible scenarios ahead; where you can systematically process all your research and in-house knowledge into a decision analysis model that matches your investment process, and prompts you to improve it; where you can align client allocation objectives with your investment behaviour in a predictive and reliable framework, delivering on your investment mandate with fewer surprises.

SAPIAT enables this new world with a powerful unbiased, comprehensive and actionable analytical solution that supports and aligns all key enterprise decision makers – executive, investment and risk teams –helping to transform any investment business into a more agile, resilient and profitable enterprise.