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n8n Postgres pgvector Consent Check + OpenAI Embeddings, Slack Alerts

n8n Postgres pgvector Consent Check + OpenAI Embeddings, Slack Alerts

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n8n Postgres pgvector Consent Check + OpenAI Embeddings, Slack Alerts

n8n Postgres pgvector Consent Check + OpenAI Embeddings, Slack Alerts

Regular price £68.99
Regular price £68.99 Sale price
SAVE Sold out

Nightly PGVector embeddings only when consent allows—plus Slack alerts

This n8n workflow automatically reads unindexed knowledge base records from Postgres, checks each one against a Postgres consent register, and only generates OpenAI embeddings to store in pgvector when the required lawful conditions are satisfied. Decisions (included, refused, or held) are logged to a manifest and the workflow posts a summary to Slack whenever any records are refused or held.

What this workflow does

  • Runs nightly on a schedule to keep your pgvector index up to date.
  • Reads unindexed documents from kb_documents (using indexed_at to identify what still needs embedding).
  • Loads consent information from a separate consent_register table in Postgres.
  • Per-record consent matching & eligibility checks evaluate whether each document is eligible based on:
    • Required purpose
    • Retention window
    • Withdrawal status
    • Profiling objections
    • Special category flags
  • Embeds only eligible text: eligible documents are chunked, embedded via OpenAI, and inserted into your pgvector index table with metadata.
  • Writes an inclusion manifest entry recording the decision and lawful ground; marks eligible documents as indexed in Postgres.
  • Logs refused/held decisions to the same manifest table with the specific refusal/hold ground.
  • Posts a run report to Slack when any records are refused or held.

Use cases

  • Keeping a consent-aware knowledge base index in sync for RAG search using pgvector.
  • Preventing embedding of withdrawn or non-eligible records before they enter vector search.
  • Operational compliance monitoring: Slack alerts highlight refused/held items for review.

Technical details

  • Postgres integration: reads kb_documents + consent_register, stores vectors in a pgvector table, and writes to index_manifest.
  • OpenAI embeddings: generates embeddings for eligible document chunks (model name must match your OpenAI access).
  • Slack OAuth: sends notifications when refusals/holds occur.
  • Workflow nodes/logic include: if, set, code, no op, merge, and slack.
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