Adds semantic code search to AI coding agents, enabling natural language queries across entire codebases to retrieve relevant code chunks, saving tokens and providing deep context.
Provides AI coding agents with persistent architectural memory of codebases, enabling impact analysis, test generation, and code generation with reduced token usage.
Transforms codebases into a knowledge graph for AI agents, enabling semantic search, impact analysis, and persistent session memory with up to 94% token savings.
Provides semantic code search and retrieval capabilities for AI agents, enabling them to query codebases using natural language with automatic learning, hybrid search, and intelligent chunking of functions and classes.
Provides persistent, local-first memory with knowledge graph and hybrid search for AI coding agents, reducing token usage by storing decisions, patterns, and codebase context.
Provides AI agents with causal code memory by indexing repositories into a graph of symbols and edges, enabling context-aware retrieval of relevant code slices.