Clean text,
from messy real documents.
Real-world documents aren't clean text — PDFs with multi-column layouts, scanned pages, embedded tables. Unstructured.io parses these into structured, usable text before they ever reach a RAG pipeline's embedding step.
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The step before
embedding, not after.
A RAG pipeline is only as good as the text it retrieves from — and most real documents aren't clean, single-column text. Unstructured.io handles the parsing work: extracting text from PDFs, Word documents, HTML, and scanned pages while preserving structure like tables and headers, so the chunking and embedding steps downstream have something sensible to work with.
We pair it with ChromaDB or LlamaIndex depending on what the rest of the pipeline needs.
Parsing that preserves
structure, not just text.
Getting the text out is easy. Preserving what it means is the actual work.
Tables, headers, and multi-column layouts parsed with their structure intact, not flattened into a word soup.
PDFs, Word documents, HTML, and scanned images handled through one consistent pipeline.
Output structured so the chunking strategy downstream can actually respect document boundaries.
Where this fits
The preprocessing step underneath any RAG pipeline working with real documents.
Before you
book a call.
The questions we get asked most about document parsing for RAG — answered straight, no sales pitch.
Why not just extract text with a basic PDF library?
Basic extraction often loses structure — a table becomes a jumble of numbers, a two-column layout interleaves unrelated sentences. Unstructured.io preserves that structure, which matters directly for retrieval quality downstream.
Does this handle scanned documents?
It handles common formats including scanned images, often paired with OCR tooling like Tesseract for documents that are pure images of text.
How does this fit into a RAG build?
It's the preprocessing step before chunking and embedding — clean, structured text in, so the rest of the pipeline has something sensible to retrieve from.
Tell us what
documents you're working with.
Book a 30-minute call — we'll tell you honestly whether your documents need this level of parsing, or whether something simpler works.