AI-Assisted Data Reconciliation at Scale: Patterns for Distributed Systems

In any sufficiently large distributed system, data reconciliation is the dark matter of engineering — invisible, pervasive, and holding everything together through mechanisms nobody fully understands. Rule-based reconciliation works until it doesn't. Rule engines break on ambiguity, cannot handle semantic equivalence across schema versions, and generate false positives at scale that overwhelm operations teams. AI — specifically embedding-based similarity and LLM classification — fills the gap....