From Documents to Context: Designing Effective Chunking in Data 360
Same documents, different AI answers. The culprit isn't the model—it's how you chunk.
Why it matters
A practical deep-dive into document chunking and retrieval strategies within Salesforce Data 360. Practitioners building RAG systems need to understand how parsing, indexing, and retrieval design drive AI quality—not just model choice.
The key facts
8 to knowChunking strategy (parsing, division, enrichment, indexing, retrieval) materially affects AI output quality
Same input documents can yield different results based on preparation pipeline
Salesforce Data 360 product context
Published August 2026
Document parsing and chunking strategy affects AI output quality independent of model choice
Includes enrichment, indexing, and retrieval pipeline design
Salesforce Data 360 feature/product focus
Published as vendor technical guidance (blog post)
Go to the source
Salesforce Blogsalesforce.com
Publisher excerpt: Two organizations can ingest the same documents and receive dramatically different AI responses. The difference may not be the model. It can be how the content was parsed, divided, enriched, indexed, and retrieved.…