Every RAG demo works on a clean text file. Then you point it at real enterprise documents — a scanned contract, a multi-column datasheet, a financial statement with nested tables, a PDF that’s really just photos of pages — and it falls apart. The retrieval is only as good as the parsing, and generic parsing turns rich documents into scrambled text.

Garbage in, confident-sounding garbage out. Grounding an agent you can trust doesn’t begin at the model. It begins at the document itself.

Purpose-built IDP engines

Vastvic’s intelligent document processing uses engines built specifically for hard documents — MinerU, Docling, PaddleOCR — rather than a one-size PDF-to-text pass. Together they handle the cases that break naive pipelines:

  • Layout-aware parsing of multi-column and complex page structures.
  • OCR for scans and images embedded inside PDFs.
  • Table and figure extraction with structure preserved, not flattened.

If the parsing loses the table, no amount of clever prompting will get the number back.

Source-grounded, not paraphrased

Extraction is only half the job; provenance is the other half. Every extracted fact carries a source span you can click back to. When an app answers “Q3 pricing rose 8% on the Pro tier,” it can point at page 4 of the pricing PDF — a citation, not a vibe.

That traceability is what makes the output usable in settings where being wrong has consequences: finance, compliance, operations.

Extract exactly what you need

Beyond retrieval, you can define a schema in plain language and have Vastvic extract source-grounded values across an entire corpus — vendor, total, line items — ready for human review, validation gates, and downstream automation.

The same grounded context then feeds everything else: your agents, your workflows, and the apps App Foundry generates. Grounding isn’t a bolt-on; it’s the foundation the rest stands on.

The payoff is answers your team can defend, because every one traces back to the document it came from — and a pipeline that holds up on the messy documents your business actually runs on, not just the clean ones in the demo.

Key takeaways

  • Retrieval quality is capped by parsing quality — grounding starts at the document.
  • MinerU, Docling and PaddleOCR handle layouts, scans, images-in-PDF and tables.
  • Every fact carries a clickable source span — citations, not guesses.
  • Schema-driven extraction feeds agents, workflows and generated apps.