Mycelium Semantic Filter

Example Use Cases

• 1

  Filter and classify semantic knowledge from embedding vectors.

• 2

  Discover semantic relationships and affinities across multiple data sources.

• 3

  That require structured summaries and cluster analysis of knowledge data.

Description

Mycelium processes embedding vectors and text through a biological ecosystem simulation where nodes interact over multiple ticks to classify knowledge into categories such as pure, merged, loner, redundant, or dead. It supports integration with Qdrant collections and runs entirely in-memory without requiring a dedicated Qdrant instance. The system outputs various formats suitable for AI agents and knowledge management, enabling semantic filtering, clustering, and cross-file affinity analysis.