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
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
Use crawler firstCollect clean source pages before they are chunked, embedded, or indexed.Open Read RAG guideReview the practical website-to-RAG source preparation workflow.Open Document preparationPlan how file extraction and metadata attach to downstream retrieval workflows.Open Ask about RAG prepContact support for pipeline-readiness, RAG prep, or enterprise source-data questions.Open
Pipeline overview
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
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
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.
Broader automation remains gated
Stored-source retrieval and supported document workflows exist today; broader connector-driven RAG/ETL automation remains a roadmap surface until separately launch-ready.