Bayesian updates in continuous causal discovery

In today’s AI-driven enterprises, it's no longer enough for systems to detect correlations—they must continuously uncover causality to support proactive, reliable decision-making. That’s where Bayesian updates meet causal discovery.

Preview

As knowledge bases evolve and new data streams in, Bayesian reasoning offers a principled way to refine causal graphs in real time—enabling AI agents to adapt their inferences, not just their outputs. In this post, we explore how modern AI systems can use Bayesian updating to perform continuous causal inference across documents, process intelligence, and operational data—unlocking next-level insight and resilience.

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Conclusion

Coming soon

• Business-in-loop
• Comparison
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And call for actions.