Discover cause and effect to drive better decision-making.
Access a state-of-the-art Causal AI toolbox allowing you to answer the toughest business questions in a trusted and explainable way.
Collaborate to learn your causal graph.
Collaboration is key to developing an accurate representation of the cause and effect relationships within your data. decisionOS provides you with a range of causal discovery algorithms to learn your causal graph from data. decisionOS then provides a simplified user interface for domain experts to add, edit, and review causal relationships. This allows for a rapid and iterative discovery making use of both state of the art algorithms and deep domain expertise.
CausalWorkflow
.discover_causal_graph(data, config)
Build trusted models.
Many machine learning initiatives fail due to a lack of trust. decisionOS builds trust using white-box causal models which can be readily explained: allowing you to drive to the “why” of model outcomes. Constraints placed on models act as guardrails to prevent unexpected behaviors, while human expertise enforces models which better capture real world phenomena.
Leverage our doubleML package to build robust causal models – learn more.
from causalnet import CausalNet cnet = CausalNet() cnet.train(...) cnet .interventions .do(...)
Translate model output into quantitative, actionable recommendations.
Causal models enable interventions and counterfactuals to be calculated. These allow you to answer “why” and “what-if” questions about business critical scenarios.
Decision Intelligence Engines use interventions and counterfactuals to translate model output to quantitative, actionable recommendations.
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Causal Effects
Quantify how interventions impact different groups within your data.
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Algorithmic Recourse
Provide optimal interventions for a given objective.
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Causal Fairness & Bias
Determine how discrimination can occur within your data as you perform interventions and actions.
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Root Cause Analysis
Understand the underlying reasons for why certain outcomes occur.
Causal AI Features
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Expansive Causal Ecosystem
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Open Source Integrations
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Self Service Development
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SOC2 & HIPAA Data Protection
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Scalable Kubernetes Compute
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Multi-Cloud Native
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Pre-built Templates and Examples
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Powerful Time Series Engine
Frequently Asked Questions
Ways to get started
Book a demo
Book a personalized demo to see our decision-making AI powered by Causal AI in action.
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Resources
Read our white papers, case studies, and research to gain new understanding in the world of Causality.
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