khive
An open-source knowledge graph for AI agents that helps developers turn information into structured, queryable context and relationships instead of relying only on vector stores or generic semantic search.
Tool overview
The safest current read is that khive is an early open-source knowledge-graph layer for AI agents, not a broadly validated search platform or finished knowledge product. The strongest evidence comes from the official GitHub repository wording, which supports its intended role around structured context beyond vectors, but does not prove production reliability, retrieval quality, performance gains, or ecosystem maturity.
Practically, the repo describes it as something agents can build, query, and grow as a knowledge graph, organizing entities, relationships, and traceable context. It is not a general-purpose search engine and not an out-of-the-box enterprise knowledge-base SaaS. A better analogy is a graph-based context layer or structured memory layer for agents. That makes sense for teams that care about multi-hop relations, long-term memory, or more structured reasoning flows.
On cost and adoption, the evidence only supports that it is open source, which is visible from the official repo.
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