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Semantic Deduplication

CPU-optimized semantic clustering engine achieving ~34% token reduction for RAG pipelines via SimHash and graph clustering.

Semantic Deduplication workflow: Input text → Semantic matching → Graph clustering → ChromaDB store → Deduplicated text. Vector persistence · Similarity analysis · Token efficiency.

Optimization Engine · Role: R&D

Architecture

  • SimHash near-duplicate prefiltering
  • NetworkX graph clustering
  • ChromaDB persistence

Results & scale

  • 33.9% character reduction avg
  • Fast CPU-based processing

Technology stack

  • Python
  • NetworkX
  • ChromaDB
  • SentenceTransformers

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