decisionOS enables organizations to gain true business value by embedding Causal AI into their decision-making workflows.
> Extract Knowledge:
Uncover cause and effect then transform causal drivers into explainable models.
> Build decision-making applications:
Use the decisionApp SDK to create customized full stack decision-making applications.
> Operationalize decision workflows:
Connect with other systems to create seamless executable decision workflows.
decisionOS enables organizations to leverage Causal AI, the only technology that can reason about cause-and-effect relationships. Causal reasoning unlocks higher forms of machine intelligence that go beyond predictions and directly enhance human decision-making.
Identify the cause and effect relationships within your data using a wide range of powerful causal discovery algorithms designed to function rapidly even on complex data. decisionOS combines the best causal discovery algorithms from our R&D lab and the wider open source community. Enable cross-functional collaboration by allowing subject-matter experts to inject domain expertise to enhance causal discovery, via an intuitive user interface.
Transform causal drivers into an explainable model that represents cause-effect relationships and their functional forms. decisionOS provides novel architectures for building structural causal models or causally-enabled decision trees to maximize performance and trustworthiness. decisionOS is extensible with all popular open-source software packages, giving data scientists the freedom to build models with any software.
Transform model outputs from predictions to actionable recommendations, by orchestrating interventions and counterfactuals. Our flagship causal decision intelligence engines include:
Build applications that are customized to the way your business users prefer to consume information, rapidly and with full flexibility.
Connect with other software systems and data sources to create seamless executable decision workflows
Transparency and explainability of AI models requires an understanding of causality—an inherent advantage of the causaLens platform”
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.”
Causal AI is a fundamental scientific breakthrough and causaLens’ vision for Causal AI extends far beyond enterprise decision making. causaLens has the potential to disrupt a vast range of sectors and industries and has already demonstrated the value of its Causal AI technology in biological applications such as the discovery of cancer biomarkers”
*This should be taken as a personal statement and not a statement or endorsement from Mayo Clinic. Mayo Clinic does not support or endorse any commercial products or companies and never has.
Causal AI plays an ever more important role in our investment analysis. It empowers our strategists and portfolio managers to generate alpha by identifying new causal relationships in economic, financial and alternative data, with sophisticated, adaptive and explainable models that don’t suffer from overfitting.”
The novel Causal AI techniques available on the causaLens Platform have facilitated our joint effort of discovering valuable profitable trading strategies”
The causaLens platform plays an important role in our investment process and has helped us generate outsized returns. It yields transparent and explainable models that we have confidence in, as they are based on causal relationships”
causaLens provides us with key causal insights that continuously unlock untapped value in our data.”