arXiv cs.AIWednesday · May 27, 2026FREE

ORCA: An End-to-End Interactive Copilot for Optimized Root Cause Analysis

causal-analysiscopilotagentsroot-cause-analysis

ORCA, introduced in arXiv paper 2605.27022, is a copilot for end-to-end causal analysis that orchestrates agents to understand user goals and guide them through appropriate workflows, from fully automatic to highly user-guided execution. It features causal discovery, causal effect estimation, explainability, and root-cause analysis (RCA). ORCA evaluates and compares performance, generates key metrics and diagrams, and produces structured reports with insights. The system is designed to make causal methods accessible to domain experts in fields like manufacturing, social science, and medicine. Its effectiveness is demonstrated across several real-world use-cases, enabling experts to leverage advanced causal analysis without deep methodological expertise.

// why it matters

Makes causal analysis accessible to domain experts without requiring deep methodological knowledge.

Sources

Primary · arXiv cs.AI
▸ Read original at arxiv.org

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