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Where pgvector fits
Searching approved documents within a PostgreSQL-backed application.
When to choose another approach
Similarity search does not prove a statement is correct, current or authorized for a reader.
Worked example and evidence
Fictional support portal: approved documents → versioned chunks → permission-filtered retrieval → answer with citations. Withdrawn content is removed from retrieval.
What you need to supply
Document owners, customer boundaries, permissions, update policy, embedding provider and evaluation questions.
What acceptance should demonstrate
Verify cross-customer access rejection, citation accuracy, document withdrawal and answers to unsupported questions.
Running costs and responsibilities
Assign embedding costs, index maintenance, document freshness, model evaluation and access reviews.
Technical scope to confirm
Filtering and approximate-index behaviour must be measured together for the real query pattern.
A proposal should identify the systems and data, direction of sync, access feasibility, failure handling, named owners and included deliverables. Listing this technology does not imply a prebuilt connector, vendor partnership or included feature.
How do we prevent answers from another customer’s documents?
Enforce tenant and document permissions before context reaches the model, then verify with deliberately forbidden cross-customer requests. A prompt alone is insufficient.