Postgres Retrieval Architecture: Multi-Tenant SaaS Help Center Schema Design
Short answer: use a staged retrieval design with explicit collections, bounded queries, and traceable source context, then make index cost a schema input rather than a vendor-selection afterthought. For a gaming help center, the expensive unit is not “an article.” It is every indexed representation of an article section, multiplied by tenant boundaries, locales, active embedding versions,…
Designing a retrieval architecture for a multi-tenant SaaS help center schema in Postgres involves several key considerations. First and foremost, the retrieval unit should be the smallest source section that can be independently cited, refreshed, and deleted. This means avoiding whole page updates and arbitrary token windows, as they make targeted updates expensive and citations vague.
To achieve this, the schema should record minimum contract components, including tenant_id, source_id, canonical_ref, and updated_at. This ensures that one source section can be refreshed without altering its identity. Additionally, an embedding_record should be created whenever a section needs a new embedding, allowing two model versions to coexist during a bounded migration.
When comparing retrieval architectures, it's crucial to count the number of retrieval units before selecting a product. This U * L * V * E formula represents the planning quantity, where U is the number of independently citable content units, L is the number of indexed locales, V is the number of embedding versions kept live during a migration, and E is the number of indexed environments. This metric helps expose which schema choices duplicate vectors and aids in budgeting the index multiplier.
A hybrid policy can isolate large tenants and group smaller ones, but the collection assignment must be stored in the schema. Temporary copies should be included in the migration budget rather than assuming an instant move. Content hashes keep ingestion repeatable, and stable unit_id values preserve citation identity when text is re-embedded.
In summary, the retrieval architecture should prioritize the smallest possible retrieval unit, record tenant_id and relevant index keys, and treat the vector index as a replaceable projection. This approach ensures that retrieval quality comes first while maintaining traceable source context and budgeting the index multiplier effectively.
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