CocoIndex

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At a glance

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Overlap and shared capabilities

Both Worlds and CocoIndex address the need for structured, indexable context over Markdown documents. Both systems parse section headings, chunk content for search, and maintain fast retrieval pipelines so AI agents spend fewer tokens retrieving relevant context. The difference is in which layer of the stack they manage:

• CocoIndex is an incremental ETL sidecar pipeline. It continuously watches source files and updates derived pgvector or WASM PGlite vector indexes.
• Worlds is an authoritative RDF fact engine. It manages canonical triple assertions, SHACL shapes, SPARQL graph filters, and immutable provenance.

Rather than competing, the two systems serve complementary steps in the context pipeline: CocoIndex handles background incremental indexing, while Worlds provides the authoritative SPARQL-driven knowledge ledger.

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When Worlds fits

• You need deterministic graph querying (SPARQL) to verify multi-hop relationships across enterprise domain facts.
• You require immutable provenance and audit trails for every assertion.
• You want open-standard RDF schemas that operate natively across edge adapters (LibSQL) and cloud databases.

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When CocoIndex fits

• You want an incremental background pipeline that updates vector embeddings as Markdown files change.
• You need zero-Docker local vector sidecars via WASM PGlite.
• You are transforming raw document corpora into derived chunk indexes for LLM RAG pipelines.

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Coexistence and integration

CocoIndex and Wazoo tooling work together out of the box. You can use CocoIndex directly alongside the Wiki toolchain, as demonstrated in the official wiki-cocoindex-template, where Wiki CLI manages markdown source checking and CocoIndex builds derived sidecar vector indexes. As projects and team memory scale, we recommend integrating Worlds as the central context engine, letting CocoIndex handle background incremental vector indexing while Worlds serves authoritative, SPARQL-driven graph retrieval.