Technical Validation for AI Research Teams
Benchmarks and A/B evaluation showing how CragData improves RAG ingestion and agent research—numbers, honest coverage limits, and reproduction steps.
Web intelligence engineering
Crawling infrastructure, AI retrieval, anti-bot systems, and RAG freshness—written for builders.
Web Scraping vs Live Web Intelligence
Why production AI teams outgrow scrape scripts and need managed crawl, graph, and freshness layers.
Read article →Crawl Orchestration With Queues
How CragData queues discover and crawl jobs, handles retries, and delivers graph updates without you running workers.
Read article →Why AI Agents Need Live Web Crawling
Static training data cannot power production agents. Live crawl, graph, and extract pipelines keep RAG grounded in today's web.
Read article →Static Datasets Are Dying
Why RAG teams are moving from snapshot dumps to live crawl pipelines with queues, graphs, and structured extraction.
Read article →Building RAG With Live Web Data
A concrete pipeline for RAG with niche graphs, top pages, structured scrape JSON, and embeddings.
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