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.

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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

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

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