Semantic Code Search Via Vector Embeddings And Symbol Graph

via “semantic memory search with vector and graph-based retrieval”

Universal memory layer for AI Agents

Unique: Supports both vector-based semantic search (24+ vector store providers) and graph-based entity/relationship search (multiple graph store providers) with a unified API, allowing developers to choose or combine retrieval strategies. Includes configurable similarity thresholds and reranking to optimize result quality without requiring manual prompt engineering.

vs others: More flexible than pure vector search (Pinecone, Weaviate) because it adds graph-based relationship traversal, and more practical than pure graph search because it combines semantic similarity scoring with structural queries, enabling both fuzzy and precise memory retrieval.