D · Digital Products · AI Assets & Agents
RAG Knowledge Bases
RAG knowledge bases are curated, chunked document collections ready to ground an assistant in a specific domain. Their value depends on source licensing, freshness and preparation quality, so check provenance, chunking strategy, embedding model and how often the content is refreshed.
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Buyer guide
- Review the source list and confirm redistribution rights for every source included.
- Check the vector format and embedding model match your retrieval stack, or that raw chunks are included for re-embedding.
What to compare
- 01Domain and source coverage
- 02Source licensing and provenance
- 03Chunking and metadata
- 04Embedding model and vector format
- 05Refresh cadence
Use cases
- Grounding a support or research assistant