Automated RAG vector store sync

Automated RAG vector store sync (n8n + Supabase pgvector)

The problem: a retrieval-augmented chatbot whose knowledge base drifts out of date the moment the source docs change — unless someone remembers to manually re-embed everything.

What I built: a fully automated reindex pipeline in n8n that keeps the vector store current with zero manual steps.

How it works:

Triggers on a daily schedule and on a deploy webhook

Fetches source markdown, chunks it on heading boundaries with overlap to preserve context

Embeds in batches via a Supabase Edge Function (384-dim)

Bulk UPSERTs vectors into Postgres with pgvector

Removes stale chunks from deleted or shortened docs automatically

Why it's solid:

Idempotent — safe to re-run any number of times, no duplicates, no drift

Runs entirely on free tiers ($0 infra)

Retry-on-fail on network calls + a dedicated error workflow for alerts

I design and ship production automations like this — RAG pipelines, data sync, internal tooling, and API integrations. If you're building anything with AI retrieval or you've got a repetitive data process worth automating, send me a message and let's scope it.