# Crawlbase shows how to build an incremental RAG index with its Enterprise Crawler, webhooks, and pgvector

> Crawlbase published a blog post detailing a method for incremental RAG indexing that uses scheduled recrawling, content hashing, and selective re-embedding via webhooks and pgvector.

- Canonical: https://extractfeed.io/story/crawlbase-shows-how-to-build-an-incremental-rag-index-with-i-4899765/
- JSON: https://extractfeed.io/api/v1/stories/crawlbase-shows-how-to-build-an-incremental-rag-index-with-i-4899765.json
- Beat: Extraction & Parsing · Evidence: Primary source · Type/significance: analysis/2 · First seen: 2026-10-03T00:40:19.779185+00:00 · Updated: 2026-10-03T00:40:19.779185+00:00 · Edition: 2026-11-05
- Framing: model-written (headline, standfirst, why it matters, tags); source facts deterministic

## Briefing
- Crawlbase: Crawlbase published a blog post detailing a method for incremental RAG indexing that uses scheduled recrawling, content hashing, and selective re-embedding via webhooks and pgvector.

## Why it matters
This post addresses a common pain point in RAG pipelines: the cost and latency of re-embedding unchanged content. By demonstrating a hash-based change detection approach with webhooks, Crawlbase offers a practical pattern that reduces redundant computation and keeps vector indexes fresh without full rebuilds. It signals a growing convergence between web crawling infrastructure and vector database workflows.

## Sources
- Primary source · Crawlbase · 2026-10-02 — [Incremental RAG Indexing](https://crawlbase.com/blog/incremental-rag-index-with-crawler-webhooks-and-pgvector/)

## Watch next
Will other crawler vendors add native change-detection hooks for vector databases?

Topics: Crawlbase, pgvector, rag, incremental-indexing, webhooks, pgvector, enterprise-crawler, content-hashing

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