Web data for RAG pipelines
Collect public web content as Markdown for retrieval-augmented generation. Use bounded AIHackr crawls, source URLs and your own ingestion pipeline.
On this page
From public page to retrievable source
Use AIHackr to collect text, then bring your own chunking, embeddings, vector database and retrieval layer. A Markdown response gives you a readable starting point; the source metadata helps you trace a retrieved passage back to its webpage.
- Choose an authoritative public source and inspect one page.
- Map its links or crawl a bounded section.
- Save content, source URL and observation time together.
- Remove repetitive navigation, deduplicate and chunk by headings.
- Embed and index in your own application.
- Test retrieval with questions and expected supporting passages.
Control scope before increasing coverage
Set a small crawl limit and an appropriate depth. Save complete results before the seven-day retention window ends. Inspect truncation and failed page outcomes before indexing. Retrieval quality depends on your source selection and downstream processing; AIHackr does not provide a hosted vector database or a guaranteed answer-quality score.
Start with one source
Read the web-to-RAG guide or follow the API quickstart. Begin with one page and evaluate the content before spending the rest of your trial.