Implementing semantic deduplication with vector similarity
Exact-match deduplication misses the majority of real-world duplicates because humans rephrase, reorder, and abbreviate content in countless ways. Semantic deduplication uses vector embeddings to find near-duplicate content regardless of surface-level differences, and this guide shows how to implement it at scale with pgvector and Python.
embeddingsdeduplicationvector-similaritypgvectordata-quality
17 July 2026