RAG data preparation

RAG pipeline prep for cleaner source-of-truth data

Reliable RAG starts before the model answers. SourceOfTruth.io focuses on the upstream work: collecting the right sources, preserving evidence, cleaning content, and preparing material for chunking, indexing, and retrieval.

Quick actions
Pipeline overview
RAG workflow

Start with cleaner inputs

RAG quality depends on source quality. The crawler-first workflow helps teams collect cleaner public source sets before indexing begins.

  • Targeted URLs
  • Bounded crawls
  • Clean exports
  • Source evidence
Discuss workflow
RAG workflow

Separate collection from preparation

Crawler work, document processing, chunking, embedding, and retrieval each have different costs. SourceOfTruth.io keeps those responsibilities distinct.

  • Crawler metering
  • Document processing
  • Embedding usage
  • Vector search
Discuss workflow
RAG workflow

Make retrieval easier to inspect

Good RAG systems need traceable source material. Clean source exports and job history make it easier to inspect what went into the pipeline.

  • Job history
  • Exports
  • Evidence snapshots
  • Customer review
Discuss workflow
What this page means today

Source collection

The live crawler collects web content with estimates, credits, and clean exports.

Review before indexing

Markdown, JSON, and CSV output should be human-reviewable before retrieval work starts.

Chunking and embeddings

These are downstream RAG preparation steps, not the same thing as the crawler itself.

Future production pipeline

Broader RAG/ETL automation remains a roadmap surface until launch-ready.

Crawler-first positioning remains active.This page explains RAG preparation direction without implying unlimited or fully launched ETL/RAG automation.