back_office_ops · workflow
The case for using structured and semi-structured data in generative AI
Most discussions of generative AI assume unstructured data, but organizations also hold large amounts of structured and semi-structured data in SaaS applications and operational databases that they want to query with AI.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Extract and vectorize table text
Text-rich fields from structured tables are extracted and vectorized to turn structured data into unstructured data for AI use.
Tools used
Fivetranvector databases
Outcome
(not stated)
Grounding & classification
Source type: generic use case
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